Model comparison
Mistral Large 2 vs Qwen3.6-27B
Head-to-head evidence from 11 shared benchmark results across 5 categories. Overall scores shown here use the public BenchAlign v5 ranking lane.
Public leaderboard positions: Mistral Large 2 #163 (Estimated); Qwen3.6-27B #93 (Estimated). Intervals and evidence labels describe ranking uncertainty, not a guarantee for a specific workload.
Evidence parity. Mistral Large 2 and Qwen3.6-27B share 11 comparable benchmark results. 0 of 8 categories are comparable. 0 results are unique to Mistral Large 2; 43 to Qwen3.6-27B.
Updated July 21, 2026- Shared results
- 11
- Mistral Large 2 only
- 0
- Qwen3.6-27B only
- 43
- Comparable categories
- 0 / 8
Benchmark data for Mistral Large 2 and Qwen3.6-27B is coming soon on BenchLM.
Confidence note. This is a partial-evidence comparison with 11 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.
Qwen3.6-27B has the larger context window at 262K, compared with 128K for Mistral Large 2.
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 | Mistral Large 2 | Δ | Qwen3.6-27B |
|---|---|---|---|
| Agentic | Mistral Large 2Not measured | MarginNo overlap | Qwen3.6-27B59.3 |
| Coding | Mistral Large 2Not measured | MarginNo overlap | Qwen3.6-27B77.5 |
| Knowledge | Mistral Large 2Not measured | MarginNo overlap | Qwen3.6-27B53.3 |
| Math | Mistral Large 2Not measured | MarginNo overlap | Qwen3.6-27B89.2 |
| Multimodal | Mistral Large 2Not measured | MarginNo overlap | Qwen3.6-27B76.7 |
Operational comparison
Runtime and commercial metrics are compared only when both models have a complete sourced value.
| Metric | Mistral Large 2 | Qwen3.6-27B | Comparison |
|---|---|---|---|
| Input / output priceUSD per 1M tokens | Mistral Large 2Not available | Qwen3.6-27B$0 input / $0 output | A complete price comparison is not available. |
| Generation speedtokens per second | Mistral Large 238 tok/s | Qwen3.6-27BNot available | A complete speed comparison is not available. |
| First-answer latencyseconds to first token | Mistral Large 21.45 s | Qwen3.6-27BNot available | A complete latency comparison is not available. |
| Context windowmaximum listed tokens | Mistral Large 2128K | Qwen3.6-27B262K | Qwen3.6-27B lists the larger context window. |
Benchmark Deep Dive
Agentic10 benchmarks
| Benchmark | Mistral Large 2 | Qwen3.6-27B | Result |
|---|---|---|---|
| τ²-bench resultsSource | 30.7% | 94.2% | Qwen3.6-27B leads |
| Terminal-Bench 2.0Source | — | 59.3% | Not comparable |
| Claw-EvalSource | — | 72.4% | Not comparable |
| QwenClawBenchSource | — | 53.4% | Not comparable |
| QwenWebBenchSource | — | 1487 | Not comparable |
| AndroidWorldSource | — | 70.3% | Not comparable |
| AA Agentic IndexSource | — | 27.0% | Not comparable |
| GDPval-AASource | — | 32.0% | Not comparable |
| GDPval-AASource | — | 1140 | Not comparable |
| Gert LabsSource | — | 54.84% | Not comparable |
Coding8 benchmarks
| Benchmark | Mistral Large 2 | Qwen3.6-27B | Result |
|---|---|---|---|
| AA-SciCodeSource | 29.2% | 39.8% | Qwen3.6-27B leads |
| SWE-bench VerifiedSource | — | 77.2% | Not comparable |
| SWE MultilingualSource | — | 71.3% | Not comparable |
| SWE-bench ProSource | — | 53.5% | Not comparable |
| Terminal-Bench 2.0Source | — | 59.3% | Not comparable |
| LiveCodeBenchSource | — | 83.9% | Not comparable |
| NL2RepoSource | — | 36.2% | Not comparable |
| AA Coding IndexSource | — | 53.7% | Not comparable |
Reasoning2 benchmarks
Knowledge12 benchmarks
| Benchmark | Mistral Large 2 | Qwen3.6-27B | Result |
|---|---|---|---|
| Artificial Analysis Intelligence IndexSource | 9.2% | 37.0% | Qwen3.6-27B leads |
| AA-GPQA DiamondSource | 48.6% | 84.2% | Qwen3.6-27B leads |
| AA-HLESource | 4.0% | 21.6% | Qwen3.6-27B leads |
| AA-Omniscience IndexSource | -34.0% | -19.8% | Qwen3.6-27B leads |
| AA-Omniscience AccuracySource | 20.1% | 19.2% | Mistral Large 2 leads |
| AA-Omniscience Hallucination RateSource | 67.8% | 48.3% | Qwen3.6-27B leads |
| MMLU-ProSource | — | 86.2% | Not comparable |
| MMLU-ReduxSource | — | 93.5% | Not comparable |
| SuperGPQASource | — | 66% | Not comparable |
| C-EvalSource | — | 91.4% | Not comparable |
| GPQASource | — | 87.8% | Not comparable |
| HLESource | — | 24% | Not comparable |
Math5 benchmarks
Multimodal16 benchmarks
| Benchmark | Mistral Large 2 | Qwen3.6-27B | Result |
|---|---|---|---|
| MMMUSource | — | 82.9% | Not comparable |
| MMMU-ProSource | — | 75.8% | Not comparable |
| RealWorldQASource | — | 84.1% | Not comparable |
| DynaMathSource | — | 85.6% | Not comparable |
| MStarSource | — | 81.4% | Not comparable |
| SimpleVQASource | — | 56.1% | Not comparable |
| CharXivSource | — | 78.4% | Not comparable |
| CC-OCRSource | — | 81.2% | Not comparable |
| CountBenchSource | — | 97.8% | Not comparable |
| RefCOCO (avg)Source | — | 92.5% | Not comparable |
| ERQASource | — | 62.5% | Not comparable |
| Video-MME (with subtitle)Source | — | 87.7% | Not comparable |
| VideoMMMUSource | — | 84.4% | Not comparable |
| MLVU (M-Avg)Source | — | 86.6% | Not comparable |
| V*Source | — | 94.7% | Not comparable |
| AA-MMMU-ProSource | — | 74.6% | Not comparable |
Inst. Following1 benchmarks
| Benchmark | Mistral Large 2 | Qwen3.6-27B | Result |
|---|---|---|---|
| AA-IFBenchSource | 31.2% | 67.6% | Qwen3.6-27B leads |
Frequently Asked Questions (3)
Can I compare Mistral Large 2 and Qwen3.6-27B 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 2 and Qwen3.6-27B today?
Mistral Large 2: Pricing unavailable Qwen3.6-27B: $0.00 input / $0.00 output per 1M tokens 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.
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