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Model comparison

Mistral Large 3 vs Qwen3.7 Max

Data verified

Head-to-head evidence from 15 shared benchmark results across 5 categories. Overall scores shown here use the public BenchAlign v5 ranking lane.

50.4/100
Margin
22.4pts
winning →
72.84/100
0 category wins0 category wins

Public leaderboard positions: Mistral Large 3 #113 (Supported); Qwen3.7 Max #10 (Supported). Intervals and evidence labels describe ranking uncertainty, not a guarantee for a specific workload.

Evidence parity. Mistral Large 3 and Qwen3.7 Max share 15 comparable benchmark results. 0 of 8 categories are comparable. 1 result is unique to Mistral Large 3; 43 to Qwen3.7 Max.

Updated July 23, 2026
Shared results
15
Mistral Large 3 only
1
Qwen3.7 Max only
43
Comparable categories
0 / 8

Benchmark data for Mistral Large 3 and Qwen3.7 Max is coming soon on BenchLM.

Confidence note. This is a partial-evidence comparison with 15 shared benchmark results across 5 evidence categories; 0 of 8 categories currently have scoreable aggregates for both models. Treat the verdict as directional until coverage is more balanced.

Why this result

BenchLM has partial data for these models, but not enough overlapping benchmark coverage to produce a fair score-level comparison yet.

Qwen3.7 Max has the larger context window at 1M, compared with 128K for Mistral Large 3.

Category breakdown

Exact category averages are shown below. Not measured means BenchLM does not have enough sourced public coverage for that model and category.

Category scores and score margins for Mistral Large 3 and Qwen3.7 Max
CategoryMistral Large 3ΔQwen3.7 Max
AgenticMistral Large 3Not measuredMarginNo overlapQwen3.7 Max69.7
CodingMistral Large 3Not measuredMarginNo overlapQwen3.7 Max77.9
ReasoningMistral Large 3Not measuredMarginNo overlapQwen3.7 Max90.4
KnowledgeMistral Large 3Not measuredMarginNo overlapQwen3.7 Max64.2
MathMistral Large 3Not measuredMarginNo overlapQwen3.7 Max97.1
MultilingualMistral Large 3Not measuredMarginNo overlapQwen3.7 Max87.0
Inst. FollowingMistral Large 3Not measuredMarginNo overlapQwen3.7 Max84.4

Operational comparison

Runtime and commercial metrics are compared only when both models have a complete sourced value.

MetricMistral Large 3Qwen3.7 MaxComparison
Input / output priceUSD per 1M tokensMistral Large 3$0.5 input / $1.5 outputQwen3.7 MaxNot availableA complete price comparison is not available.
Generation speedtokens per secondMistral Large 348 tok/sQwen3.7 MaxNot availableA complete speed comparison is not available.
First-answer latencyseconds to first tokenMistral Large 31.04 sQwen3.7 MaxNot availableA complete latency comparison is not available.
Context windowmaximum listed tokensMistral Large 3128KQwen3.7 Max1MQwen3.7 Max lists the larger context window.

Benchmark Deep Dive

Agentic
BenchmarkMistral Large 3Qwen3.7 MaxResult
AA Agentic IndexSource 5.5%30.6%Qwen3.7 Max leads
τ²-bench resultsSource 24.6%94.7%Qwen3.7 Max leads
GDPval-AASource 6.6%38.7%Qwen3.7 Max leads
GDPval-AASource 6331273Qwen3.7 Max leads
Terminal-Bench 2.0Source 69.7%Not comparable
QwenClawBenchSource 64.3%Not comparable
QwenWebBenchSource 1568Not comparable
Claw-EvalSource 65.2%Not comparable
BFCL v4Source 75.0%Not comparable
MCP AtlasSource 76.4%Not comparable
VITA-BenchSource 47.9%Not comparable
HLE w/ toolsSource 53.5%Not comparable
Gert LabsSource 64.27%Not comparable
ResearchClawBenchSource 18.7%Not comparable
AA BriefcaseSource 908Not comparable
AA AutomationBenchSource 25.6%Not comparable
AA EnterpriseOps-GymSource 45.0%Not comparable
AA ITBenchSource 42.5%Not comparable
terminalBenchHardSource 50.8%Not comparable
aaTerminalBench21Source 74.5%Not comparable
AA Harvey LABSource 83.4%Not comparable
Coding
BenchmarkMistral Large 3Qwen3.7 MaxResult
AA Coding IndexSource 20.1%66.0%Qwen3.7 Max leads
AA-SciCodeSource 36.2%48.8%Qwen3.7 Max leads
SWE-bench VerifiedSource 80.4%Not comparable
SWE-bench ProSource 60.6%Not comparable
SWE MultilingualSource 78.3%Not comparable
NL2RepoSource 47.2%Not comparable
SciCodeSource 53.5%Not comparable
LiveCodeBenchSource 91.6%Not comparable
Terminal-Bench 2.0Source 69.7%Not comparable
Reasoning
BenchmarkMistral Large 3Qwen3.7 MaxResult
AA-LCRSource 34.7%69.0%Qwen3.7 Max leads
CritPtSource 0.0%13.4%Qwen3.7 Max leads
MRCRv2Source 90.4%Not comparable
Knowledge
BenchmarkMistral Large 3Qwen3.7 MaxResult
Artificial Analysis Intelligence IndexSource 15.9%46.0%Qwen3.7 Max leads
AA-GPQA DiamondSource 68.0%92.3%Qwen3.7 Max leads
AA-HLESource 4.1%38.1%Qwen3.7 Max leads
AA-Omniscience IndexSource -39.4%14.1%Qwen3.7 Max leads
AA-Omniscience AccuracySource 24.1%30.1%Qwen3.7 Max leads
AA-Omniscience Hallucination RateSource 83.7%22.9%Qwen3.7 Max leads
GPQASource 92.4%Not comparable
GPQA-DSource 92.4%Not comparable
HLESource 41.4%Not comparable
MMLU-ProSource 89.6%Not comparable
MMLU-ReduxSource 95%Not comparable
SuperGPQASource 73.6%Not comparable
MMMLUSource 90.3%Not comparable
Math
BenchmarkMistral Large 3Qwen3.7 MaxResult
HMMT Feb 2026Source 97.1%Not comparable
IMOAnswerBenchSource 90.0%Not comparable
ApexSource 44.5%Not comparable
Multilingual
BenchmarkMistral Large 3Qwen3.7 MaxResult
MMLU-ProXSource 87%Not comparable
NOVA-63Source 59.0%Not comparable
INCLUDESource 86.2%Not comparable
MAXIFESource 89.2%Not comparable
PolyMathSource 86.5%Not comparable
Multimodal
BenchmarkMistral Large 3Qwen3.7 MaxResult
AA-MMMU-ProSource 55.7%Not comparable
Design Arena WebsiteSource 1293Not comparable
Inst. Following
BenchmarkMistral Large 3Qwen3.7 MaxResult
AA-IFBenchSource 36.2%80.5%Qwen3.7 Max leads
IFEvalSource 94.3%Not comparable
IFBenchSource 79.1%Not comparable
Frequently Asked Questions (3)

Can I compare Mistral Large 3 and Qwen3.7 Max on BenchLM yet?

Not fully yet. BenchLM is tracking both models, but the sourced benchmark breakdown for this comparison is still coming soon.

Why does this comparison show “coming soon”?

BenchLM only shows category winners and benchmark-level calls when we have sourced results that can be compared fairly. For these models, the public benchmark coverage is not complete enough yet.

What data is available for Mistral Large 3 and Qwen3.7 Max today?

Mistral Large 3: $0.50 input / $1.50 output per 1M tokens Qwen3.7 Max: Pricing unavailable Both model pages still include creator, context window, reasoning mode, and other metadata while benchmark coverage fills in.

Self-host vs API cost

Estimates at 50,000 req/day · 1000 tokens/req average.

Mistral Large 3
API / mo$1,500
Self-host / mo$9,110
Break-even380M/day
Qwen3.7 Max
API / mo$0
Self-host / moNot listed
Break-even
Proprietary model — self-hosting not applicable.
Model the full break-even

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Last updated: July 23, 2026

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