RankingEffort benchmarks

Mistral Medium 3.5 · Reasoning

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33 measured results · 3 effort settings · 33 benchmark/harness combinations

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Capability profile

One configuration, seven capabilities

Comparison score · 0–100

AMistral Medium 3.5 · Reasoning3 of 7 capabilities supported

Gaps are unknown, not zero. Hollow points are preliminary.

Agentic
A16.0Supported
Hard reasoning
A7.1Supported
Coding
A13.9Preliminary
Human pref
Unknown
Knowledge
A15.7Supported
Multimodal
A8.1Preliminary
Long context
A15.4Preliminary

Each profile belongs to the named configuration. Capability scores use a shared panel for all axes, distinct from the overall ranking panel; they are not accuracy percentages or direct head-to-head wins.

Capability score evidence

Mistral Medium 3.5 · Reasoning: 5.3 overall comparison score. Meets the overall evidence requirements.

6 areas measured. The available task mix affects this estimate; missing areas remain unknown.

Which sources carry the weight?

Artificial Analysis · 100.0% direct comparison weight · independent of the model provider

Which benchmark families carry the weight?

IFBench · 7.6% direct comparison weight
Humanity’s Last Exam · 7.4% direct comparison weight
GPQA · 7.4% direct comparison weight
Critpt · 7.4% direct comparison weight
omniscience · 7.4% direct comparison weight
Other families (10) · 62.7% direct comparison weight

These shares describe direct comparison weight, not fractions of the final score or confidence. Source balancing does not give every family equal weight or remove correlations between overlapping sources.

How sensitive is this score?

The audit removes one source at a time and refits against the same overall reference panel. These published results use the matching dataset audited 2026-10-20.

Both ranks use the same surviving configurations for each removal. The cohort starts with 444 configurations supported in the original audit, including separate effort settings. These are diagnostic positions, not the default leaderboard ranks. Eligibility is not rechecked after removal.

What changes when a source is removed?
Removed source	Rank before → after	Rank movement	Cohort remaining / lost support	Score after (change)
Artificial Analysis	Comparison support lost; no rank		203 remaining / 241 lost	Unavailable
ARC Prize	237 → 237	No movement	444 remaining / 0 lost	6.8 (+1.5 points)
Datacurve	237 → 238	Down 1	444 remaining / 0 lost	4.1 (-1.1 points)
LiveCodeBench	237 → 237	No movement	444 remaining / 0 lost	5.2 (-0.1 points)
Scale	237 → 237	No movement	444 remaining / 0 lost	6.2 (+0.9 points)
Terminal-Bench	237 → 237	No movement	444 remaining / 0 lost	5.2 (-0.1 points)
Cognition	237 → 239	Down 2	444 remaining / 0 lost	5.1 (-0.2 points)
LiveBench	236 → 235	Up 1	443 remaining / 1 lost	5.5 (+0.2 points)
SWE-rebench	237 → 237	No movement	444 remaining / 0 lost	5.4 (+0.1 points)
Epoch AI	231 → 231	No movement	431 remaining / 13 lost	5.4 (+0.2 points)
Vals AI	237 → 236	Up 1	443 remaining / 1 lost	5.1 (-0.2 points)
Provider reports · Anthropic	237 → 237	No movement	444 remaining / 0 lost	5.3 (-0.0 points)
Provider reports · Moonshot AI	237 → 238	Down 1	444 remaining / 0 lost	5.1 (-0.2 points)
Provider reports · Meta	237 → 237	No movement	444 remaining / 0 lost	5.3 (-0.0 points)
Provider reports · Mistral	237 → 237	No movement	444 remaining / 0 lost	5.3 (+0.0 points)
Provider reports · OpenAI	237 → 237	No movement	444 remaining / 0 lost	5.3 (+0.0 points)
All provider reports	237 → 238	Down 1	444 remaining / 0 lost	5.1 (-0.1 points)

Lost support means a configuration no longer has a comparison path to the complete reference panel. Its rank is unavailable. A surviving path alone does not establish leaderboard eligibility.

Overlapping sources may remain correlated even with source balancing. Leave-one-source-out movement is a sensitivity diagnostic, not a spread of source-specific ranks or a confidence measure. Scoring methodology · Dated configuration audit

Every benchmark family

Removed evidence	Recomputed score	Change
arc-agi	6.5	+1.3
deepswe	4.2	-1.1
critpt	6.2	+0.9
mmmu-pro	5.9	+0.7
tau-bench	4.7	-0.5
hle	5.8	+0.5
ifbench	4.7	-0.5
gdp-pdf	5.6	+0.3
enterprise-ops	5.0	-0.3
omniscience	5.0	-0.3
epoch-game-puzzles	5.0	-0.3
simpleqa	5.5	+0.3
frontiercode	5.1	-0.2
mmlu-pro	5.4	+0.2
swe-rebench	5.4	+0.1
automationbench	5.1	-0.1
livebench-instructions	5.4	+0.1
multi-swe-bench	5.2	-0.1
gpqa	5.4	+0.1
analyst-agent	5.2	-0.1
apex-agents	5.4	+0.1
terminal-bench-science	5.4	+0.1
livebench-language	5.4	+0.1
arc-agi-3	5.2	-0.1
aa-lcr	5.2	-0.1
enigma-eval	5.2	-0.1
terminal-bench	5.2	-0.1
swe-atlas-qna	5.2	-0.1
livebench-coding	5.2	-0.1
gdpval	5.2	-0.1
harvey	5.2	-0.1
itbench	5.2	-0.0
livebench-reasoning	5.2	-0.0
vibe-code	5.2	-0.0
gmmlu	5.3	+0.0
aime	5.2	-0.0
math500	5.3	+0.0
swe-atlas-test-writing	5.2	-0.0
vals-code-migration	5.2	-0.0
vals-finance-agent	5.2	-0.0
vals-legal-research	5.2	-0.0
livecodebench	5.3	-0.0
vals-tax-agent	5.3	-0.0
briefcase	5.3	-0.0
vals-excel-modeling	5.3	-0.0
livebench-math	5.3	+0.0
frontiermath	5.3	+0.0
swe-atlas-refactoring	5.3	-0.0
livebench-data	5.3	-0.0
swe-bench-pro	5.3	+0.0

What evidence is missing from the fit?

Across all collected settings for this model: 48 observations, 28 contributing, 0 matched without graph weight and 20 excluded. Counts do not establish rank eligibility.

1 · Benchmark family or source protocol has not been reviewed
1 · Original SciCode grading defects are under review; retained as supporting evidence, excluded from aggregate and capability scores. Corrected SciCode-Verified requires a separate protocol review. Sources: https://arxiv.org/abs/2608.04975 and https://artificialanalysis.ai/evaluations/scicode
2 · The evaluator reports no named effort control. This does not identify a non-reasoning configuration.
1 · Effort is not identified
3 · No matched, identified effort unit; duplicates and unnamed comparators do not add evidence
9 · Supporting evidence outside the reviewed capability core
2 · No reviewed effort for this catalog observation; any separately collected effort measurement is counted separately
1 · No matched opponent in this evaluation unit

Inspect every observation and exclusion →

Benchmark results

These are published benchmark scores. Supported effort estimates also appear on the Capability leaderboard. Results from different harnesses occupy different rows. Missing cells stay unknown; no scores are copied between effort levels.

Benchmark / source	High	Reasoning	Unspecified
AA-AnalystAgentArtificial Analysis · Artificial Analysis published evaluation; see source for benchmark-specific settings Benchmark details Share of tasks solved on all 5 of 5 attempts · 80 tasks, 5 attempts per task · Independently benchmarked by Artificial Analysis · Evaluation results measured independently by Artificial Analysis Unit: percent. Source collected 2026-10-18.	Not reported	12.5% Reported settings Mistral Medium 3.5; Reported effort: reasoning; Model source: https://artificialanalysis.ai/models/mistral-medium-3-5; Mode from evaluator isReasoning metadata; effort budget not specified	Not reported
AA-Briefcase EloArtificial Analysis · Artificial Analysis published evaluation; see source for benchmark-specific settings Benchmark details AA-Briefcase v1.1 is an agentic knowledge work benchmark developed by Artificial Analysis. AA-Briefcase Elo is a combined metric that aggregates rubric pass rate, analytical quality Elo and presentation Elo · Higher is better · Evaluation results measured independently by Artificial Analysis Unit: elo. Source collected 2026-10-18.	Not reported	522.97 Elo Reported settings Mistral Medium 3.5; Reported effort: reasoning; Model source: https://artificialanalysis.ai/models/mistral-medium-3-5; Mode from evaluator isReasoning metadata; effort budget not specified	Not reported
AA-LCR v1.1Artificial Analysis · Artificial Analysis published evaluation; see source for benchmark-specific settings Benchmark details Independently benchmarked by Artificial Analysis · Evaluation results measured independently by Artificial Analysis Unit: percent. Source collected 2026-10-18.	Not reported	69.33% Reported settings Mistral Medium 3.5; Reported effort: reasoning; Model source: https://artificialanalysis.ai/models/mistral-medium-3-5; Mode from evaluator isReasoning metadata; effort budget not specified	Not reported
AutomationBench-AAArtificial Analysis · Artificial Analysis published evaluation; see source for benchmark-specific settings Benchmark details Share of task objectives completed with no guardrail violations · Higher is better · Benchmark developed by Zapier · Independently benchmarked by Artificial Analysis · Evaluation results measured independently by Artificial Analysis Unit: percent. Source collected 2026-10-18.	Not reported	6.3% Reported settings Mistral Medium 3.5; Reported effort: reasoning; Model source: https://artificialanalysis.ai/models/mistral-medium-3-5; Mode from evaluator isReasoning metadata; effort budget not specified	Not reported
CritPtArtificial Analysis · Artificial Analysis published evaluation; see source for benchmark-specific settings Benchmark details Benchmark developed by Argonne and UIUC, with contributions from 60+ researchers globally. CritPt is under review by its authors following external feedback · Independently benchmarked by Artificial Analysis · Evaluation results measured independently by Artificial Analysis Unit: percent. Source collected 2026-10-18.	Not reported	0% Reported settings Mistral Medium 3.5; Reported effort: reasoning; Model source: https://artificialanalysis.ai/models/mistral-medium-3-5; Mode from evaluator isReasoning metadata; effort budget not specified	Not reported
EnterpriseOps-Gym-AAArtificial Analysis · Artificial Analysis published evaluation; see source for benchmark-specific settings Benchmark details Overall task success rate across all eight enterprise domains (oracle tool mode) · Benchmark developed by ServiceNow Research · Independently benchmarked by Artificial Analysis · Evaluation results measured independently by Artificial Analysis Unit: percent. Source collected 2026-10-18.	Not reported	33.72% Reported settings Mistral Medium 3.5; Reported effort: reasoning; Model source: https://artificialanalysis.ai/models/mistral-medium-3-5; Mode from evaluator isReasoning metadata; effort budget not specified	Not reported
GDP.pdf: All-pass RateArtificial Analysis · Artificial Analysis published evaluation; see source for benchmark-specific settings Benchmark details Share of attempts where every atomic criterion passed · Independently benchmarked by Artificial Analysis · Evaluation results measured independently by Artificial Analysis Unit: percent. Source collected 2026-10-18.	Not reported	2.8% Reported settings Mistral Medium 3.5; Reported effort: reasoning; Model source: https://artificialanalysis.ai/models/mistral-medium-3-5; Mode from evaluator isReasoning metadata; effort budget not specified	Not reported
GDPval-AA v2.1 LeaderboardArtificial Analysis · Artificial Analysis published evaluation; see source for benchmark-specific settings Benchmark details Elo rating for performance on real-world work tasks · Anchored to DeepSeek V4.1 Flash (max) at 1600 · Higher is better · Evaluation results measured independently by Artificial Analysis Unit: elo. Source collected 2026-10-18.	Not reported	760.86 Elo Reported settings Mistral Medium 3.5; Reported effort: reasoning; Model source: https://artificialanalysis.ai/models/mistral-medium-3-5; Mode from evaluator isReasoning metadata; effort budget not specified	Not reported
GPQA DiamondArtificial Analysis · Artificial Analysis published evaluation; see source for benchmark-specific settings Benchmark details Independently benchmarked by Artificial Analysis · Evaluation results measured independently by Artificial Analysis Unit: percent. Source collected 2026-10-18.	Not reported	74.85% Reported settings Mistral Medium 3.5; Reported effort: reasoning; Model source: https://artificialanalysis.ai/models/mistral-medium-3-5; Mode from evaluator isReasoning metadata; effort budget not specified	Not reported
Humanity's Last ExamArtificial Analysis · Artificial Analysis published evaluation; see source for benchmark-specific settings Benchmark details Independently benchmarked by Artificial Analysis · Evaluation results measured independently by Artificial Analysis Unit: percent. Source collected 2026-10-18.	Not reported	13.76% Reported settings Mistral Medium 3.5; Reported effort: reasoning; Model source: https://artificialanalysis.ai/models/mistral-medium-3-5; Mode from evaluator isReasoning metadata; effort budget not specified	Not reported
IFBenchArtificial Analysis · Artificial Analysis published evaluation; see source for benchmark-specific settings Benchmark details Independently benchmarked by Artificial Analysis · Evaluation results measured independently by Artificial Analysis Unit: percent. Source collected 2026-10-18.	Not reported	68.78% Reported settings Mistral Medium 3.5; Reported effort: reasoning; Model source: https://artificialanalysis.ai/models/mistral-medium-3-5; Mode from evaluator isReasoning metadata; effort budget not specified	Not reported
MLCR-AAArtificial Analysis · Artificial Analysis published evaluation; see source for benchmark-specific settings Benchmark details Share of tasks judged accurate, complete, and concise · Expert + compound (hard) sets · Benchmark developed by Wisedocs · Independently benchmarked by Artificial Analysis · Evaluation results measured independently by Artificial Analysis Unit: percent. Source collected 2026-10-18.	Not reported	1.67% Reported settings Mistral Medium 3.5; Reported effort: reasoning; Model source: https://artificialanalysis.ai/models/mistral-medium-3-5; Mode from evaluator isReasoning metadata; effort budget not specified	Not reported
MMMU-ProArtificial Analysis · Artificial Analysis published evaluation; see source for benchmark-specific settings Benchmark details Independently benchmarked by Artificial Analysis · Evaluation results measured independently by Artificial Analysis Unit: percent. Source collected 2026-10-18.	Not reported	64.86% Reported settings Mistral Medium 3.5; Reported effort: reasoning; Model source: https://artificialanalysis.ai/models/mistral-medium-3-5; Mode from evaluator isReasoning metadata; effort budget not specified	Not reported
AA-Omniscience IndexArtificial Analysis · Artificial Analysis published evaluation; see source for benchmark-specific settings Benchmark details AA-Omniscience Index (higher is better) measures knowledge reliability and hallucination. It rewards correct answers, penalizes hallucinations, and has no penalty for refusing to answer. Scores range from -100 to 100, where 0 means as many correct as incorrect answers, and negative scores mean more incorrect than correct. · Evaluation results measured independently by Artificial Analysis Unit: index. Source collected 2026-10-18.	Not reported	-36.8 Reported settings Mistral Medium 3.5; Reported effort: reasoning; Model source: https://artificialanalysis.ai/models/mistral-medium-3-5; Mode from evaluator isReasoning metadata; effort budget not specified	Not reported
AA-Omniscience AccuracyArtificial Analysis · 6000 questions; 1 attempt; correct-answer share; GPT-5.6 Luna medium grader Benchmark details AA-Omniscience Accuracy (higher is better) measures the proportion of correctly answered questions out of all questions, regardless of whether the model chooses to answer · Evaluation results measured independently by Artificial Analysis Unit: percent. Source collected 2026-10-18.	Not reported	24.67% Reported settings Mistral Medium 3.5; Reported effort: reasoning; Model source: https://artificialanalysis.ai/models/mistral-medium-3-5; Mode from evaluator isReasoning metadata; effort budget not specified	Not reported
SciCodeArtificial Analysis · Artificial Analysis published evaluation; see source for benchmark-specific settings Benchmark details Benchmark curated by scientists across 16 disciplines. SciCode is under review following an independent audit of the dataset · Independently benchmarked by Artificial Analysis · Evaluation results measured independently by Artificial Analysis Unit: percent. Source collected 2026-10-18.	Not reported	40.16% Reported settings Mistral Medium 3.5; Reported effort: reasoning; Model source: https://artificialanalysis.ai/models/mistral-medium-3-5; Mode from evaluator isReasoning metadata; effort budget not specified	Not reported
𝜏²-Bench TelecomArtificial Analysis · Artificial Analysis published evaluation; see source for benchmark-specific settings Benchmark details Independently benchmarked by Artificial Analysis · Evaluation results measured independently by Artificial Analysis Unit: percent. Source collected 2026-10-18.	Not reported	94.15% Reported settings Mistral Medium 3.5; Reported effort: reasoning; Model source: https://artificialanalysis.ai/models/mistral-medium-3-5; Mode from evaluator isReasoning metadata; effort budget not specified	Not reported
𝜏³-BankingArtificial Analysis · Artificial Analysis published evaluation; see source for benchmark-specific settings Benchmark details Benchmark developed by Sierra Research · Independently benchmarked by Artificial Analysis · Evaluation results measured independently by Artificial Analysis Unit: percent. Source collected 2026-10-18.	Not reported	15.05% Reported settings Mistral Medium 3.5; Reported effort: reasoning; Model source: https://artificialanalysis.ai/models/mistral-medium-3-5; Mode from evaluator isReasoning metadata; effort budget not specified	Not reported
Terminal-Bench HardArtificial Analysis · Artificial Analysis published evaluation; see source for benchmark-specific settings Benchmark details Independently benchmarked by Artificial Analysis · Evaluation results measured independently by Artificial Analysis Unit: percent. Source collected 2026-10-18.	Not reported	33.33% Reported settings Mistral Medium 3.5; Reported effort: reasoning; Model source: https://artificialanalysis.ai/models/mistral-medium-3-5; Mode from evaluator isReasoning metadata; effort budget not specified	Not reported
Terminal-Bench v2.1Artificial Analysis · Artificial Analysis published evaluation; see source for benchmark-specific settings Benchmark details Benchmark developed by the Laude Institute and open-source contributors · Independently benchmarked by Artificial Analysis · Evaluation results measured independently by Artificial Analysis Unit: percent. Source collected 2026-10-18.	Not reported	50.56% Reported settings Mistral Medium 3.5; Reported effort: reasoning; Model source: https://artificialanalysis.ai/models/mistral-medium-3-5; Mode from evaluator isReasoning metadata; effort budget not specified	Not reported
Terminal-Bench v4.0Artificial Analysis · mini-SWE-agent v2.4.6; 66 tasks; pass@1 averaged over 3 repeats; 500 steps; task timeout up to 8 hours Benchmark details Benchmark developed by the Laude Institute, Stanford, and open-source contributors · Independently benchmarked by Artificial Analysis · Evaluation results measured independently by Artificial Analysis Unit: percent. Source collected 2026-10-18.	Not reported	0% Reported settings Mistral Medium 3.5; Reported effort: reasoning; Model source: https://artificialanalysis.ai/models/mistral-medium-3-5; Mode from evaluator isReasoning metadata; effort budget not specified	Not reported
FrontierCode 1.1 · extended-chiselCognition · chisel Benchmark details FrontierCode 1.1; chisel. Open each result for its exact effort, task subset, metric and protocol details. Unit: percent. Source collected 2026-10-18.	Not reported	Not reported	18.66% Reported settings FrontierCode 1.1; extended; 150 tasks; chisel; source effort none; weighted rubric score, not pass rate; unfair internet runs zeroed by evaluator; flag rate 0.004 The evaluator reports no named effort control. This does not identify a non-reasoning configuration. Source label needs review
FrontierCode 1.1 · main-chiselCognition · chisel Benchmark details FrontierCode 1.1; chisel. Open each result for its exact effort, task subset, metric and protocol details. Unit: percent. Source collected 2026-10-18.	Not reported	Not reported	8% Reported settings FrontierCode 1.1; main; 100 tasks; chisel; source effort none; weighted rubric score, not pass rate; unfair internet runs zeroed by evaluator; flag rate 0.006 The evaluator reports no named effort control. This does not identify a non-reasoning configuration. Source label needs review
Vals AI · Finance Agent v2Vals AI · Vals FAB v2 shared six-tool harness; two-hour task limit Benchmark details Overall weighted rubric accuracy, averaged over three runs on 450 tasks. Dealbreaker failures and timeouts score zero. Related categories and all-pass scores are not additional votes. Three-model judge panel; private test set. Unit: percent. Source collected 2026-10-18.	32.1% Reported settings {"checkpoint":"mistral-medium-3.5","evaluatorModel":"mistralai/mistral-medium-3.5","sourceUpdatedOn":"2026-10-16","reasoning_effort":"high","compute_effort":null,"reasoning":null,"temperature":0.7,"top_p":0.95,"max_output_tokens":80000,"verbosity":null,"provider":"Mistral AI","harness":null}	Not reported	Not reported
Vals AI · Code Migration v1Vals AI · Vals Code Migration shared agent harness Benchmark details Hidden behavior-test pass rate, equally weighted across 40 repositories (30 CLI and 10 COBOL-to-Java). Anti-cheat failures score zero. Code-quality ratings and language splits are not additional votes. Unit: percent. Source collected 2026-10-18.	5.13% Reported settings {"checkpoint":"mistral-medium-3.5","evaluatorModel":"mistralai/mistral-medium-3.5","sourceUpdatedOn":"2026-10-16","reasoning_effort":"high","compute_effort":null,"reasoning":null,"temperature":0.7,"top_p":0.95,"max_output_tokens":80000,"verbosity":null,"provider":"Mistral AI","harness":null}	Not reported	Not reported

What these comparisons mean

Each source reports its own effort labels. Matching labels do not establish equal compute budgets or identical fallback behavior. Open Reported settings to inspect the exact model name, agent and task coverage. Multiple results at one level remain visible rather than selecting the best. Source-reported None or Non-reasoning labels are not treated as evidence that an API supports those settings.

These measurements use their own dated source collection. The leaderboard fits identified configurations jointly; it contains no pooled model ratings. Explicit thinking budgets are separate configurations. Read the methodology.

Download all effort benchmark results · 8,915 results across 259 models · Collected 2026-10-18

Mistral Medium 3.5 · Reasoning

Compare with

One configuration, seven capabilities

Agentic

Hard reasoning

Coding

Human pref

Knowledge

Multimodal

Long context

Capability score evidence

Benchmark results