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
46.2 / 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.
This analysis covers this configuration across its recorded thinking conditions and test suites.
Use this Instruct configuration for straightforward passage questions and small project edits you can check. Passage answers combine good accuracy with short waits, but small coding offers no clear speed advantage over successful alternatives on this test machine. Larger practical work is uneven, while handling challenged source-backed answers and difficult reasoning are substantial weaknesses. Treat it as a supervised helper rather than a dependable autonomous worker.
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.
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.
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
2026-10-22T05:53:47.604667Z
Review time
2026-10-22T05:56:50.673689+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.
Generation and editorial authorship remain attached to this revision. Changing the default generator does not change this attribution.
Good at
Answers straightforward passage questions well in a test mix that includes unanswerable questions, making it useful for extracting information from text.
Handles most bounded programming tasks in these tests, covering project-file searches, edits and bug fixes. Use it for small changes whose results you can check.
Struggles badly when source-backed answers must survive challenges or change with new evidence. Do not trust it to settle disputed facts without checking the source yourself.
Larger practical tasks often missed the target, while puzzles and difficult math-and-reasoning problems scored poorly. Exact instruction-following also needs checking; useful small-project results do not carry over to these demands.
Passage accuracy narrowly trails the leading tested medium-sized dense models; its task-time advantage over matching equally or more accurate alternatives is modest. Across sizes, several alternatives delivered better small-coding results sooner in these runs.
Reading without guessing Thinking off. Medium · 5–under 20B · dense. Tied at rank 4 of 10 in this recorded comparison.
Speed: Reading without guessing Thinking off. Matching test-machine label and execution settings; spans model sizes. Timings include unsuccessful tasks, so read them alongside quality.
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.
Reading without guessingThinking off · Medium · 5–under 20B · dense
Answer from a passage—or say that the passage does not contain the answer.
Exact-match accuracy · 0–100% · higher is better 16 of 16 tasks scored for each model.
Gaps are relative to this model. Treat small gaps cautiously.
Share of tasks that passed the recorded checks. 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.
Speed and task success: Reading without guessingThinking 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.
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
Choose Instruct for small coding: Ministral 3 8B Reasoning 2512 Q4_K_M matched its success but took longer. That separate checkpoint improved passage calculations and research-paper answer matching at substantially longer task times, yet did worse on larger practical tasks.
Share of tasks that passed the recorded checks. 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.
Calculating from a passageThinking off · Ministral 3 8B · Instruct versus reasoning checkpoint
Read a passage and count, compare or calculate using its facts.
Numeric exact-match accuracy · 0–100% · higher is better 7 of 7 tasks scored for each model.
Gaps are relative to this model. Treat small gaps cautiously.
#2Ministral 3 8B Instruct Q4_K_M8.5B total parameters57.1%
This model
How this comparison works
Share of tasks that passed the recorded checks. 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.
Reading research papersThinking off · Ministral 3 8B · Instruct versus reasoning checkpoint
Answer a question about a paper and identify the paragraphs supporting the answer.
Answer token F1 · 0–100 points · higher is better 8 of 8 tasks scored for each model.
Gaps are relative to this model. Treat small gaps cautiously.
#2Ministral 3 8B Instruct Q4_K_M8.5B total parameters31.1/100
This model
How this comparison works
Answer overlap with the reference answer; partial matches earn 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.
Larger practical tasksThinking off · Ministral 3 8B · Instruct versus reasoning checkpoint
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.
#1Ministral 3 8B Instruct Q4_K_M8.5B total parameters45.5/100
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.
Worth knowing
The requested thinking-on condition is an ineligible preview without verified switch control. No within-checkpoint thinking recommendation is supported.
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 limit readers’ 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 role-format compatibility fix, not a fresh unbiased rerun. Instruct and Reasoning are separate checkpoints, not an on/off pair.
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.
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.
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.
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.
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.
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.
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.
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.
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.
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.
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.
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.
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.
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.
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.
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.
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.
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.
Nemotron Nano 9B v2 Q4_0
Another checkpoint in the same total-parameter band and architecture category, with matching task controls.
Requested thinking off · Complete compared coverage