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Ministral 3 14B

1 tested weight format · Explore results, then inspect the answers.

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Q4_K_M · 8.24 GB download

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Setup, memory & provenance · Q4_K_M

Q4_K_M · 8.24 GB of weights · rocm · context 16384 · GPU layers 99

Medium · 5–under 20B · dense · 13.5B total

Memory fit has not been verified for this configuration.

partial

Recorded settings and thinking verification

Temperature 0 · seed 42 · output limit 4096 · reasoning effort unrecorded

RAM labels describe the test computer, not this model’s memory requirement. Speed comparisons keep the 32 GB and 128 GB runs separate.

Runtime build: unrecorded · Local · test machine with 32 GB RAM · concurrency: 1

Thinking status: ignored switch · probe 2 · scope Saved profile-level probe; exact historical template/build scope is not fully recorded..

Requested off does not prove an absence of reasoning. Saved checks do not establish unrecorded historical template or build details.

Overall across tasks

62.1 / 100

Nine categories, equally weighted · 9/9 eligible

Complete coverage for this setup. Quality only; speed is separate. How the index works →

What does it do well?

Select a category to explore the answers. Bars show what happened on every planned task. Incorrect answers and failures to finish both earn zero; technical problems and untested tasks stay unscored.

Exact scores and task times by suite

Each suite has its own metric and fixed task bank. The balanced index weights categories equally; individual scores and evidence remain available below.

Test suiteThinking offDetails
Everyday coding tasksTask pass rate
Pass rate
12/16 · 75%
Answers completed
16/16 · 100%
Correct / completed
12/16 · 75%
12 full credit4 incorrect
16/16 scored9.7s median task time · 16 measured
Larger practical tasksMean task credit
Average credit
72.7%
Full-credit rate
8/11 · 73%
Answers completed
11/11 · 100%
Full credit / completed
8/11 · 73%
8 full credit3 incorrect
11/11 scored39.6s median task time · 11 measured
Logic and number puzzlesMean puzzle credit
Average credit
28.6%
Full-credit rate
9/34 · 26%
Answers completed
34/34 · 100%
Full credit / completed
9/34 · 26%
9 full credit7 partial credit18 incorrect
34/34 scored21.2s median task time · 34 measured
Published hard problemsMean answer credit
Average credit
55.8%
Full-credit rate
6/11 · 55%
Answers completed
11/11 · 100%
Full credit / completed
6/11 · 55%
6 full credit2 partial credit3 incorrect
11/11 scored86.3s median task time · 11 measured
Following exact instructions · original campaignStrict prompt compliance
Pass rate
16/23 · 70%
Answers completed
23/23 · 100%
Correct / completed
16/23 · 70%
16 full credit7 incorrect
23/23 scored16.9s median task time · 23 measured
Reading without guessingExact-match accuracy
Pass rate
12/16 · 75%
Answers completed
16/16 · 100%
Correct / completed
12/16 · 75%
12 full credit4 incorrect
16/16 scored1.0s median task time · 16 measured
Calculating from a passageNumeric exact-match accuracy
Pass rate
6/7 · 86%
Answers completed
7/7 · 100%
Correct / completed
6/7 · 86%
6 full credit1 incorrect
7/7 scored1.4s median task time · 7 measured
Reading research papersAnswer token F1
Average credit
22.0%
Full-credit rate
0/8 · 0%
Answers completed
8/8 · 100%
Full credit / completed
0/8 · 0%
5 partial credit3 incorrect
8/8 scored9.6s median task time · 8 measured
Resisting incorrect correctionsAll-branches pass rate
Pass rate
9/12 · 75%
Answers completed
12/12 · 100%
Correct / completed
9/12 · 75%
9 full credit3 incorrect
12/12 scored1.1s median task time · 12 measured
Following exact instructions · 128 GB campaignStrict prompt complianceNot planned

Model analysis

This analysis covers this configuration across its recorded thinking conditions and test suites.

This tested Instruct setup is useful for supervised project work and calculations from passages. Most larger practical tasks succeeded, though selected retries qualify that result. Research-paper questions and logic puzzles expose substantial weaknesses. For quick small edits, a smaller tested alternative was both quicker and more successful on this machine. Choose this setup for its useful practical-task ability, rather than assuming broadly strong reasoning or a speed advantage.

Evidence for this judgment
Larger practical tasks · Thinking off
Average score72.7/100 · Mean task credit
Test coverage11 of 11 tasks scored
Task outcomes8 full credit · 0 partial · 3 no credit
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Calculating from a passage · Thinking off
Tasks passed6 of 7 (85.7%)
Test coverage7 of 7 tasks scored
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View this model’s answers, code and tool activity →

Reading research papers · Thinking off
Average score22.0/100 · Answer token F1
Test coverage8 of 8 tasks scored
Task outcomes0 full credit · 5 partial · 3 no credit
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View this model’s answers, code and tool activity →

Logic and number puzzles · Thinking off
Average score28.6/100 · Mean puzzle credit
Test coverage34 of 34 tasks scored
Task outcomes9 full credit · 7 partial · 18 no credit
Explore these test results →

View this model’s answers, code and tool activity →

Everyday coding tasks · Thinking off
Tasks passed12 of 16 (75.0%)
Test coverage16 of 16 tasks scored
Tasks timed16 tasks
Typical time per task (median)9.7 seconds
Explore these test results →

View this model’s answers, code and tool activity →

Speed: Everyday coding tasks
Thinking off. Matching test-machine label and execution settings; spans model sizes. Timings include unsuccessful tasks, so read them alongside quality.

Source limitation
Earlier tool-task failures included a strict role-alternation rejection after context compaction. A scoped compatibility amendment moved the recap into the system message while preserving tool history. Retried technical failures are selected follow-ups, not a fresh unbiased pass-rate experiment. This tested Instruct checkpoint is not a thinking-off counterpart to the incoming Reasoning checkpoint.

Speed and task success: Everyday coding tasksThinking off · Matching test-machine label and settings · Across model sizes

Shorter task time is better only when the result is useful. These times include failures, tools and grading. Token generation speed measures a different part of the work.

Compare timings and outcomes
ModelTypical task timeGeneration speedTasks passed
Gemma 4 E2B Q4_02.2 seconds16 of 16 tasks timed107.2 tokens/s5 of 1616 of 16 scored
Qwen3.5 2B Q4_K_M4.3 seconds16 of 16 tasks timed134.3 tokens/s16 of 1616 of 16 scored
Ministral 3 14BThis model9.7 seconds16 of 16 tasks timed30.8 tokens/s12 of 1616 of 16 scored

Results from this test setup, not a promise for your computer. Hardware, software, tokenizers and answer length can change the ordering. Historical runtime builds were not always captured. Comparison saved with the 2026-10-22 assessment.

Test machine: AMD Ryzen 5 5600X (6 cores / 12 threads) · AMD Radeon RX 6700 XT (12 GB VRAM) · 32 GB or 128 GB system RAM, never mixed in one timing group. Full test machine details

Summary generated by GPT Astra · · Agent reviewed by Codex · publication authorized by user

About this summary
Analyst provider
openai
Generation route
Codex CLI · codex-cli 0.163.0 · ChatGPT account
Requested model
gpt-6-astra
Returned model
Not supplied; identity is recorded from the request only.
Exact provider snapshot
Exact provider snapshot not supplied.
Reasoning effort
high
Prompt version
model-summary-reader-v8
Generation time
2026-10-22T05:49:24.424414Z
Review time
2026-10-22T05:56:50.298949+00:00
Evidence reviewer
Codex (agent)
Publication authorization
User · 2026-10-22T05:55:43.625712+00:00 · Go ahead and complete the remaining work. Spin up agents: luna, terra, sol, astra, as needed to get it done. Narrative summaries: these are the astra generated summaries? Go ahead and get those completed as well. Once all of this is done, you may push the completed result.
Originating evidence edition
dataset-5a6f96ec56c3d240cc42fa23147c1495da1be71f3ef0722c0e5f8c4f5e126a83
Analysis input hash
318cf2c257779804bffe0b67077f76e1198cadf829e6446d7b67f295adebcaea
Summary revision
summary-5fcc7daf4c33ba5d2bef0a03bc15ec4b8a50f9e63ede4c7296b3e102063170ca

Generation and editorial authorship remain attached to this revision. Changing the default generator does not change this attribution.

Good at

Useful for supervised project work, not just small edits: most larger practical tasks succeeded. Small-project editing also worked well, though selected retries after a compatibility fix qualify the tool-task results.

Evidence for this judgment
Larger practical tasks · Thinking off
Average score72.7/100 · Mean task credit
Test coverage11 of 11 tasks scored
Task outcomes8 full credit · 0 partial · 3 no credit
Explore these test results →

View this model’s answers, code and tool activity →

Everyday coding tasks · Thinking off
Tasks passed12 of 16 (75.0%)
Test coverage16 of 16 tasks scored
Explore these test results →

View this model’s answers, code and tool activity →

Source limitation
Earlier tool-task failures included a strict role-alternation rejection after context compaction. A scoped compatibility amendment moved the recap into the system message while preserving tool history. Retried technical failures are selected follow-ups, not a fresh unbiased pass-rate experiment. This tested Instruct checkpoint is not a thinking-off counterpart to the incoming Reasoning checkpoint.

Handles calculations from passages well and solves a useful share of difficult math and reasoning questions. It can help with problem-solving, provided important answers are checked.

Evidence for this judgment
Calculating from a passage · Thinking off
Tasks passed6 of 7 (85.7%)
Test coverage7 of 7 tasks scored
Explore these test results →

View this model’s answers, code and tool activity →

Published hard problems · Thinking off
Average score55.8/100 · Mean answer credit
Test coverage11 of 11 tasks scored
Task outcomes6 full credit · 2 partial · 3 no credit
Explore these test results →

View this model’s answers, code and tool activity →

Struggles with

Research-paper answers are a serious weakness: the answer-matching score was low. Do not rely on it for accurate paper-specific answers without checking the source.

Evidence for this judgment
Reading research papers · Thinking off
Average score22.0/100 · Answer token F1
Test coverage8 of 8 tasks scored
Task outcomes0 full credit · 5 partial · 3 no credit
Incorrect completed answers3 tasks
Explore these test results →

View this model’s answers, code and tool activity →

Logic and number puzzles are a poor fit: most answers were incorrect, and partial successes did little to rescue the overall result. Check puzzle deductions and plans carefully.

Evidence for this judgment
Logic and number puzzles · Thinking off
Average score28.6/100 · Mean puzzle credit
Test coverage34 of 34 tasks scored
Task outcomes9 full credit · 7 partial · 18 no credit
Incorrect completed answers18 tasks
Explore these test results →

View this model’s answers, code and tool activity →

Compared with other models

At these baselines, it ties the leading larger-task score among other tested medium-sized dense models. Difficult math/reasoning scores are also close to the leaders, but puzzle performance trails most peers.

Evidence for this judgment
Larger practical tasks · Thinking off
Average score72.7/100 · Mean task credit
Test coverage11 of 11 tasks scored
Task outcomes8 full credit · 0 partial · 3 no credit
Explore these test results →

View this model’s answers, code and tool activity →

Published hard problems · Thinking off
Average score55.8/100 · Mean answer credit
Test coverage11 of 11 tasks scored
Task outcomes6 full credit · 2 partial · 3 no credit
Explore these test results →

View this model’s answers, code and tool activity →

Logic and number puzzles · Thinking off
Average score28.6/100 · Mean puzzle credit
Test coverage34 of 34 tasks scored
Task outcomes9 full credit · 7 partial · 18 no credit
Explore these test results →

View this model’s answers, code and tool activity →

Larger practical tasks
Thinking off. Medium · 5–under 20B · dense. Tied at rank 1 of 10 in this recorded comparison.

Published hard problems
Thinking off. Medium · 5–under 20B · dense. Rank 2 of 10 in this recorded comparison.

Logic and number puzzles
Thinking off. Medium · 5–under 20B · dense. Rank 7 of 10 in this recorded comparison.

Larger practical tasksThinking off · Medium · 5–under 20B · dense

Build small apps, organize information and investigate files or web pages.

Mean task credit · 0–100 points · higher is better
11 of 11 tasks scored for each model.

Gaps are relative to this model. Treat small gaps cautiously.

  1. =1 Gemma 4 12B11.9B total parameters72.7/100
    Same score
  2. =1 Gemma 4 12B QAT Q4_011.9B total parameters72.7/100
    Same score
  3. =1 Ministral 3 14B13.5B total parameters72.7/100
    This model
  4. #4 Ornith 1.5 9B Q4_K_M9.2B total parameters54.5/100
    18.2 points lower
  5. =5 Ministral 3 8B Instruct Q4_K_M8.5B total parameters45.5/100
    27.3 points lower
  6. =5 Qwen3.5 9B9.0B total parameters45.5/100
    27.3 points lower
  7. =7 Gemma 4 E4B7.5B total parameters36.4/100
    36.4 points lower
  8. =7 Granite 4.2 8B Q4_08.8B total parameters36.4/100
    36.4 points lower
  9. #9 Nemotron Nano 9B v2 Q4_08.9B total parameters18.2/100
    54.5 points lower
  10. #10 Qwen2.5 Coder 7B Instruct Q4_K_M7.6B total parameters0.0/100
    72.7 points lower
How this comparison works

Average credit per task; partly correct results can earn partial credit. Family comparisons show the labeled Instruct and reasoning versions. Other peer comparisons use the same requested thinking setting, not necessarily each model’s best mode. Small differences on these short tests may not hold on other tasks. Peer membership varies by test coverage and compatible settings.

Comparison saved with the 2026-10-22 assessment. Task-specific results.

Published hard problemsThinking off · Medium · 5–under 20B · dense

Answer selected difficult math and reasoning questions from LiveBench.

Mean answer credit · 0–100 points · higher is better
11 of 11 tasks scored for each model.

Gaps are relative to this model. Treat small gaps cautiously.

  1. #1 Gemma 4 12B QAT Q4_011.9B total parameters56.1/100
    0.3 points higher
  2. #2 Ministral 3 14B13.5B total parameters55.8/100
    This model
  3. #3 Gemma 4 12B11.9B total parameters54.9/100
    0.9 points lower
  4. #4 Ornith 1.5 9B Q4_K_M9.2B total parameters41.7/100
    14.1 points lower
  5. #5 Qwen3.5 9B9.0B total parameters37.6/100
    18.2 points lower
  6. #6 Ministral 3 8B Instruct Q4_K_M8.5B total parameters23.6/100
    32.2 points lower
  7. #7 Granite 4.2 8B Q4_08.8B total parameters13.7/100
    42.0 points lower
  8. #8 Gemma 4 E4B7.5B total parameters9.4/100
    46.4 points lower
  9. #9 Nemotron Nano 9B v2 Q4_08.9B total parameters6.7/100
    49.1 points lower
  10. #10 Qwen2.5 Coder 7B Instruct Q4_K_M7.6B total parameters0.6/100
    55.1 points lower
How this comparison works

Average credit per task; partly correct results can earn partial credit. Family comparisons show the labeled Instruct and reasoning versions. Other peer comparisons use the same requested thinking setting, not necessarily each model’s best mode. Small differences on these short tests may not hold on other tasks. Peer membership varies by test coverage and compatible settings.

Comparison saved with the 2026-10-22 assessment. Task-specific results.

Logic and number puzzlesThinking off · Medium · 5–under 20B · dense

Solve newly generated puzzles using arithmetic, deduction and planning.

Mean puzzle credit · 0–100 points · higher is better
34 of 34 tasks scored for each model.

Gaps are relative to this model. Treat small gaps cautiously.

  1. #1 Gemma 4 12B QAT Q4_011.9B total parameters80.9/100
    52.3 points higher
  2. #2 Gemma 4 12B11.9B total parameters77.9/100
    49.4 points higher
  3. #3 Qwen3.5 9B9.0B total parameters67.6/100
    39.1 points higher
  4. #4 Ornith 1.5 9B Q4_K_M9.2B total parameters52.5/100
    24.0 points higher
  5. #5 Nemotron Nano 9B v2 Q4_08.9B total parameters30.8/100
    2.3 points higher
  6. #6 Granite 4.2 8B Q4_08.8B total parameters29.6/100
    1.0 points higher
  7. #7 Ministral 3 14B13.5B total parameters28.6/100
    This model
  8. #8 Ministral 3 8B Instruct Q4_K_M8.5B total parameters26.6/100
    1.9 points lower
  9. #9 Gemma 4 E4B7.5B total parameters14.9/100
    13.7 points lower
  10. #10 Qwen2.5 Coder 7B Instruct Q4_K_M7.6B total parameters10.7/100
    17.8 points lower
How this comparison works

Average credit per task; partly correct results can earn partial credit. Family comparisons show the labeled Instruct and reasoning versions. Other peer comparisons use the same requested thinking setting, not necessarily each model’s best mode. Small differences on these short tests may not hold on other tasks. Peer membership varies by test coverage and compatible settings.

Comparison saved with the 2026-10-22 assessment. Task-specific results.

For small edits, Qwen3.5 2B Q4_K_M passed more tasks with a substantially shorter median task time on this machine. Gemma 4 E2B Q4_0 finished sooner still, but its much lower success makes that speed less useful.

Evidence for this judgment
Everyday coding tasks · Thinking off
Tasks passed12 of 16 (75.0%)
Test coverage16 of 16 tasks scored
Tasks timed16 tasks
Typical time per task (median)9.7 seconds
Explore these test results →

View this model’s answers, code and tool activity →

Speed: Everyday coding tasks
Thinking off. Matching test-machine label and execution settings; spans model sizes. Timings include unsuccessful tasks, so read them alongside quality.

Worth knowing

The thinking-on comparison is an untested preview: the switch was ignored, so these results cannot establish a quality or speed benefit from enabling it.

Evidence for this judgment

Source limitation
Some suite/condition results are incomplete or ineligible; their observed scores are previews.

Source limitation
Some requested reasoning conditions lack verified control.

Publication redactions restrict reader inspection of some evidence.

Evidence for this judgment

Source limitation
Some selected evidence has recorded publication redactions.

Tool-task results include selected retries after a message-format compatibility fix, not a fresh unbiased rerun. This Instruct checkpoint is separate from the Reasoning checkpoint, not its thinking-off mode.

Evidence for this judgment

Source limitation
Earlier tool-task failures included a strict role-alternation rejection after context compaction. A scoped compatibility amendment moved the recap into the system message while preserving tool history. Retried technical failures are selected follow-ups, not a fresh unbiased pass-rate experiment. This tested Instruct checkpoint is not a thinking-off counterpart to the incoming Reasoning checkpoint.

How to interpret these assessments and their limitations →

One weight format is recorded for this model. Additional tested formats will appear here when available.

What changed in these results

Earlier tool-task failures included a strict role-alternation rejection after context compaction. A scoped compatibility amendment moved the recap into the system message while preserving tool history. Retried technical failures are selected follow-ups, not a fresh unbiased pass-rate experiment. This tested Instruct checkpoint is not a thinking-off counterpart to the incoming Reasoning checkpoint.

Thinking tradeoff

No verified on/off comparison is available for this configuration and test suite. Requested modes alone do not establish a controlled thinking comparison.

Instruct vs Thinking / Reasoning

Two versions of the same model family, using separate GGUF checkpoints. Compare the extra task success with the extra time. This is a version comparison, not a switch within one file.

Everyday coding tasks

Scores and times describe this task bank. Quick failures are not a speed advantage. Different execution settings are labeled.

VersionTask resultTypical task timeWeight downloadExplore
Ministral 3 14BThinking off75.0%16/16 scored9.7 seconds16/16 timed8.24 GBAnswers and code
Ministral 3 14B Reasoning 2512 Q4_K_MThinking / Reasoning version · Different or uncertain execution settings50.0%16/16 scored32.7 seconds16/16 timed8.24 GBAnswers and code

Compare

Sampled repetitions

Repeated runs are a separate experiment and never add votes to the baseline score.

Thinking off · temperature 0.6

48/48 repeats scored · 36 full-credit repeats.

16/16 questions have every planned repeat scored. Of those, 11 earned full credit on every repeat.

Recorded repetition conditions
  • Seed 202 · requested off · ignored switch
  • Seed 303 · requested off · ignored switch
  • Seed 101 · requested off · ignored switch

Everyday coding tasks: recorded outcomes

Find information in a small project, edit files and fix bugs.

12 full credit4 incorrect

Each segment counts tasks, not credit points. Partial credit varies by task.

Scoring and fixed question bank →

This model’s answers, code and tool activity

Select a question to read the original answer, tool calls and available code changes for this configuration and thinking setting.

1–16 of 16 matching questions · 16 in this version

  • Locate the Retry Limit

    The user asks where the project's retry-limit setting is defined and what value it holds. This exercises locating a named setting in code and reporting both its location and value.

    basic-T1 · primary
  • Find the Release Date

    The user asks for the release date mentioned in a project notes document. This exercises reading a specified file and extracting a particular fact rather than guessing from outside knowledge.

    basic-T2 · primary
  • Change the Retry Limit

    The user asks to change the project's retry limit to a specified value. This exercises finding the relevant setting and making a focused code edit rather than merely describing the change.

    basic-T3 · primary
  • Create an Exact One-Line File

    The user asks to create a text file containing exactly one supplied line. This exercises basic file creation and precise instruction following, including avoiding extra text in the file.

    basic-T4 · primary
  • Explain the Latest Commit

    The user asks what the most recent Git commit changed in the project. This exercises inspecting recorded changes and turning them into a clear explanation of what was modified.

    basic-T5 · primary
  • Count and Compare Python Files

    The user asks how many Python files are in the application folder and which is largest. This exercises identifying relevant files, counting them, and comparing their sizes.

    basic-T6 · primary
  • Add Readable Byte Sizes

    The user asks to add a function that converts byte counts into readable sizes and remove the related TODO comment. This exercises implementing a small utility and updating the surrounding code consistently.

    basic-T7 · primary
  • Collect TODO Comments

    The user asks to find every TODO comment in the Python code and append each to the project's task list on a separate line. This combines searching across files with collecting text into an existing document.

    basic-T8 · primary
  • Fix Code Behind a Failing Test

    The user asks to investigate a failing test and fix the application code without changing the test. This exercises diagnosing a bug while respecting an explicit limit on what may be edited.

    basic-H1 · primary
  • Rename a Function Throughout

    The user asks to rename a network function and update every place in the project that uses it. This exercises tracking references across files and making a coordinated change rather than editing only the definition.

    basic-H2 · primary
  • Find the Proxy Settings

    The user asks to find a proxy configuration file somewhere under the project's parent folder and report its host and port. This exercises searching beyond the project folder and reading configuration values.

    basic-H3 · primary
  • Locate an Error in a Log

    The user asks which error code appears in a long event log and on which line. This exercises finding a specific entry in a large file and reporting its precise location.

    basic-H4 · primary
  • Append a Final Task

    The user asks to append a supplied release-related task as the final line of an existing task list. This exercises preserving existing content while adding exact text in the requested position.

    basic-H5 · primary
  • Calculate Total Retry Waiting

    The user asks for the total time a network function spends sleeping when all attempts fail, worked out from the code. This exercises following retry logic and adding the delays along that failure path.

    basic-H6 · primary
  • Document Every Command-Line Option

    The user asks for a project readme listing every command-line option with its help text. This exercises discovering the program's available options and transferring that information into complete, source-grounded documentation.

    basic-H7 · primary
  • Undo a Commit by Editing

    The user asks to undo the latest Git commit's change by editing the file directly, without using Git to make changes. This exercises understanding a previous edit and reversing it under a method constraint.

    basic-H8 · primary
Filters change this list, not the fixed scoring denominator. Search currently covers question IDs, titles and available task explanations. Focus a control to load prompt/outcome search where this edition provides it.

Suggested comparisons

These are starting points for inspection, not claims that one setup is better. Runtime and placement differences remain visible.

Qwen3.5 9B UD-Q6_K_XL

Another checkpoint in the same total-parameter band and architecture category, with matching task controls.

Requested thinking off · Complete compared coverage

Compare these configurations →

Selection rule and evidence IDsPolicy comparisons-v3 · Template same-parameter-architecture-matching-controls
Facts: fact-bb58072f1c77808045477c91, fact-81703cf46648d0b2de523fad
Matching candidate set: fact-81703cf46648d0b2de523fad, fact-e57043e6128b693616991807, fact-e2c619b31f8a88c1472ca60e, fact-9b097653ded9dc087919acf0, fact-3f910f804bc145423c5f4359, fact-200d3a80040bda993709f78f, fact-9f9b21c2355c6bdb5b2dd393, fact-eacdd70113b5633f3f223c12, fact-1eaacebf5d4775d7901754f8, fact-5c36b6f6bfeaa5ee466506f6, fact-bef3eb6c6baa2d44e3aa0649, fact-ec911e6561843ecc14d3482a, fact-eae080b73ed21e846eaa5d1d, fact-490482dd62af02e41d2fc20e, fact-6808af8c64a1e7875a14e7a6, fact-2e2fe4760014b5b180de8620, fact-6d911759dd69ca545ee8be5c, fact-f0e7d2286cd806072751d966

Tested weights

Q4_K_M · 8.24 GB

llmware · recorded source

76ce697c065f2e40f1e8e958118b02cab38e2c10a6015f7d7908036a292dc8c8 · Exact GGUF file →Historical first-MiB hash only; not a full-file identity.

Explore the answers

Choose a suite to inspect its exact available questions, references and model answers.