Model comparison
DeepSeekMath V2 vs Mistral Medium 3.5 128B
Head-to-head evidence from 0 shared benchmark results across 0 categories. Overall scores shown here use the public BenchAlign v5 ranking lane.
Public leaderboard positions: DeepSeekMath V2 #124 (Estimated); Mistral Medium 3.5 128B unranked (Not scored). Intervals and evidence labels describe ranking uncertainty, not a guarantee for a specific workload.
Evidence parity. DeepSeekMath V2 and Mistral Medium 3.5 128B share 0 comparable benchmark results. 0 of 8 categories are comparable. 0 results are unique to DeepSeekMath V2; 25 to Mistral Medium 3.5 128B.
Updated July 27, 2026- Shared results
- 0
- DeepSeekMath V2 only
- 0
- Mistral Medium 3.5 128B only
- 25
- Comparable categories
- 0 / 8
Benchmark data for DeepSeekMath V2 and Mistral Medium 3.5 128B 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 DeepSeekMath V2 yet. This comparison is currently limited to metadata such as context window, reasoning mode, and pricing where available.
Mistral Medium 3.5 128B is priced at $1.50 input / $7.50 output per 1M tokens, versus $0.00 input / $0.00 output per 1M tokens for DeepSeekMath V2. Mistral Medium 3.5 128B has the larger context window at 256K, compared with 128K for DeepSeekMath V2.
Operational comparison
Runtime and commercial metrics are compared only when both models have a complete sourced value.
| Metric | DeepSeekMath V2 | Mistral Medium 3.5 128B | Comparison |
|---|---|---|---|
| Input / output priceUSD per 1M tokens | DeepSeekMath V2$0 input / $0 output | Mistral Medium 3.5 128B$1.5 input / $7.5 output | DeepSeekMath V2 has the lower combined listed price. |
| Generation speedtokens per second | DeepSeekMath V2Not available | Mistral Medium 3.5 128BNot available | A complete speed comparison is not available. |
| First-answer latencyseconds to first token | DeepSeekMath V2Not available | Mistral Medium 3.5 128BNot available | A complete latency comparison is not available. |
| Context windowmaximum listed tokens | DeepSeekMath V2128K | Mistral Medium 3.5 128B256K | Mistral Medium 3.5 128B lists the larger context window. |
Benchmark Deep Dive
Agentic11 benchmarks
| Benchmark | DeepSeekMath V2 | Mistral Medium 3.5 128B | Result |
|---|---|---|---|
| τ³-bench resultsSource | — | 91.4% | Not comparable |
| AA Agentic IndexSource | — | 19.0% | Not comparable |
| τ²-bench resultsSource | — | 94.2% | Not comparable |
| GDPval-AASource | — | 21.6% | Not comparable |
| GDPval-AASource | — | 933 | Not comparable |
| Gert LabsSource | — | 39.10% | Not comparable |
| AA EnterpriseOps-GymSource | — | 33.7% | Not comparable |
| AA Harvey LABSource | — | 69.1% | Not comparable |
| terminalBenchHardSource | — | 33.3% | Not comparable |
| AA BriefcaseSource | — | 516 | Not comparable |
| AA Tau3 BankingSource | — | 14.4% | Not comparable |
Coding3 benchmarks
Reasoning2 benchmarks
Knowledge7 benchmarks
| Benchmark | DeepSeekMath V2 | Mistral Medium 3.5 128B | Result |
|---|---|---|---|
| Artificial Analysis Intelligence IndexSource | — | 29.9% | Not comparable |
| AA-GPQA DiamondSource | — | 74.8% | Not comparable |
| AA-HLESource | — | 12.8% | Not comparable |
| AA-Omniscience IndexSource | — | -36.3% | Not comparable |
| AA-Omniscience AccuracySource | — | 25.1% | Not comparable |
| AA-Omniscience Hallucination RateSource | — | 82.0% | Not comparable |
| AA Openness IndexSource | — | 33.3% | Not comparable |
Multimodal1 benchmarks
| Benchmark | DeepSeekMath V2 | Mistral Medium 3.5 128B | Result |
|---|---|---|---|
| AA-MMMU-ProSource | — | 64.9% | Not comparable |
Inst. Following1 benchmarks
| Benchmark | DeepSeekMath V2 | Mistral Medium 3.5 128B | Result |
|---|---|---|---|
| AA-IFBenchSource | — | 68.8% | Not comparable |
Frequently Asked Questions (3)
Can I compare DeepSeekMath V2 and Mistral Medium 3.5 128B 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 DeepSeekMath V2 and Mistral Medium 3.5 128B today?
DeepSeekMath V2: $0.00 input / $0.00 output per 1M tokens Mistral Medium 3.5 128B: $1.50 input / $7.50 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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