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Model comparison

Mistral 8x7B vs Qwen3.5 397B

Data verified

Head-to-head evidence from 0 shared benchmark results across 0 categories. Overall scores shown here use the public BenchAlign v5 ranking lane.

No sourced benchmark result is currently shared by both models. This page therefore compares only the available metadata, pricing, and runtime rows; it does not name a quality winner.
N/A
No comparison
57.01/100
0 category wins0 category wins

Public leaderboard positions: Mistral 8x7B #146 (Estimated); Qwen3.5 397B #71 (Estimated). Intervals and evidence labels describe ranking uncertainty, not a guarantee for a specific workload.

Evidence parity. Mistral 8x7B and Qwen3.5 397B share 0 comparable benchmark results. 0 of 8 categories are comparable. 0 results are unique to Mistral 8x7B; 55 to Qwen3.5 397B.

Updated July 22, 2026
Shared results
0
Mistral 8x7B only
0
Qwen3.5 397B only
55
Comparable categories
0 / 8

Benchmark data for Mistral 8x7B and Qwen3.5 397B is coming soon on BenchLM.

Confidence note. This is a partial-evidence comparison with 0 shared benchmark results across 0 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 does not have sourced benchmark coverage for Mistral 8x7B yet. This comparison is currently limited to metadata such as context window, reasoning mode, and pricing where available.

Qwen3.5 397B is priced at $0.60 input / $3.60 output per 1M tokens, versus $0.00 input / $0.00 output per 1M tokens for Mistral 8x7B. Qwen3.5 397B has the larger context window at 128K, compared with 32K for Mistral 8x7B.

Operational comparison

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

MetricMistral 8x7BQwen3.5 397BComparison
Input / output priceUSD per 1M tokensMistral 8x7B$0 input / $0 outputQwen3.5 397B$0.6 input / $3.6 outputMistral 8x7B has the lower combined listed price.
Generation speedtokens per secondMistral 8x7BNot availableQwen3.5 397B96 tok/sA complete speed comparison is not available.
First-answer latencyseconds to first tokenMistral 8x7BNot availableQwen3.5 397B2.44 sA complete latency comparison is not available.
Context windowmaximum listed tokensMistral 8x7B32KQwen3.5 397B128KQwen3.5 397B lists the larger context window.

Benchmark Deep Dive

Agentic
BenchmarkMistral 8x7BQwen3.5 397BResult
Terminal-Bench 2.0Source 52.5%Not comparable
BrowseCompSource 62%Not comparable
Claw-EvalSource 56.8%Not comparable
QwenClawBenchSource 51.8%Not comparable
τ³-bench resultsSource 68.4%Not comparable
VITA-BenchSource 43.7%Not comparable
DeepPlanningSource 37.6%Not comparable
ToolathlonSource 36.3%Not comparable
MCP AtlasSource 46.1%Not comparable
MCP-TasksSource 74.2%Not comparable
WideResearchSource 74.0%Not comparable
τ²-bench resultsSource 95.6%Not comparable
Gert LabsSource 46.76%Not comparable
ResearchClawBenchSource 14.2%Not comparable
AA Agentic IndexSource 19.9%Not comparable
APEX-Agents-AASource 15.3%Not comparable
GDPval-AASource 23.1%Not comparable
GDPval-AASource 962Not comparable
Coding
BenchmarkMistral 8x7BQwen3.5 397BResult
SWE-bench VerifiedSource 76.2%Not comparable
LiveCodeBench v6Source 83.6%Not comparable
SWE-bench ProSource 50.9%Not comparable
AA-SciCodeSource 42.0%Not comparable
AA Coding IndexSource 48.2%Not comparable
Reasoning
BenchmarkMistral 8x7BQwen3.5 397BResult
LongBench v2Source 63.2%Not comparable
AI-NeedleSource 68.7%Not comparable
AA-LCRSource 65.7%Not comparable
CritPtSource 1.7%Not comparable
Knowledge
BenchmarkMistral 8x7BQwen3.5 397BResult
GPQASource 88.4%Not comparable
SuperGPQASource 70.4%Not comparable
MMLU-ProSource 87.8%Not comparable
MMLU-ReduxSource 94.9%Not comparable
C-EvalSource 93%Not comparable
HLESource 28.7%Not comparable
Artificial Analysis Intelligence IndexSource 33.7%Not comparable
AA-GPQA DiamondSource 89.3%Not comparable
AA-HLESource 27.3%Not comparable
AA-Omniscience IndexSource -29.8%Not comparable
AA-Omniscience AccuracySource 31.4%Not comparable
AA-Omniscience Hallucination RateSource 89.1%Not comparable
Math
BenchmarkMistral 8x7BQwen3.5 397BResult
AIME26Source 93.3%Not comparable
HMMT Feb 2025Source 94.8%Not comparable
HMMT Nov 2025Source 92.7%Not comparable
HMMT Feb 2026Source 87.9%Not comparable
MMAnswerBenchSource 80.9%Not comparable
Multilingual
BenchmarkMistral 8x7BQwen3.5 397BResult
MMLU-ProXSource 84.7%Not comparable
NOVA-63Source 59.1%Not comparable
Multimodal
BenchmarkMistral 8x7BQwen3.5 397BResult
MMMU-ProSource 79%Not comparable
MathVisionSource 88.6%Not comparable
CharXivSource 80.8%Not comparable
VideoMMMUSource 84.7%Not comparable
ScreenSpot ProSource 65.6%Not comparable
V*Source 95.8%Not comparable
AA-MMMU-ProSource 77.3%Not comparable
Inst. Following
BenchmarkMistral 8x7BQwen3.5 397BResult
IFEvalSource 92.6%Not comparable
AA-IFBenchSource 78.8%Not comparable
Frequently Asked Questions (3)

Can I compare Mistral 8x7B and Qwen3.5 397B 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 8x7B and Qwen3.5 397B today?

Mistral 8x7B: $0.00 input / $0.00 output per 1M tokens Qwen3.5 397B: $0.60 input / $3.60 output per 1M tokens Both model pages still include creator, context window, reasoning mode, and other metadata while benchmark coverage fills in.

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Last updated: July 22, 2026

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