Model comparison
DeepSeek V3.2 (Thinking) vs Mistral Large 3
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: DeepSeek V3.2 (Thinking) #65 (Estimated); Mistral Large 3 #113 (Supported). Intervals and evidence labels describe ranking uncertainty, not a guarantee for a specific workload.
Evidence parity. DeepSeek V3.2 (Thinking) and Mistral Large 3 share 0 comparable benchmark results. 0 of 8 categories are comparable. 2 results are unique to DeepSeek V3.2 (Thinking); 16 to Mistral Large 3.
Updated July 22, 2026- Shared results
- 0
- DeepSeek V3.2 (Thinking) only
- 2
- Mistral Large 3 only
- 16
- Comparable categories
- 0 / 8
Benchmark data for DeepSeek V3.2 (Thinking) and Mistral Large 3 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 has partial data for these models, but not enough overlapping benchmark coverage to produce a fair score-level comparison yet.
DeepSeek V3.2 (Thinking) is priced at $0.55 input / $2.19 output per 1M tokens, versus $0.50 input / $1.50 output per 1M tokens for Mistral Large 3.
Operational comparison
Runtime and commercial metrics are compared only when both models have a complete sourced value.
| Metric | DeepSeek V3.2 (Thinking) | Mistral Large 3 | Comparison |
|---|---|---|---|
| Input / output priceUSD per 1M tokens | DeepSeek V3.2 (Thinking)$0.55 input / $2.19 output | Mistral Large 3$0.5 input / $1.5 output | Mistral Large 3 has the lower combined listed price. |
| Generation speedtokens per second | DeepSeek V3.2 (Thinking)Not available | Mistral Large 348 tok/s | A complete speed comparison is not available. |
| First-answer latencyseconds to first token | DeepSeek V3.2 (Thinking)Not available | Mistral Large 31.04 s | A complete latency comparison is not available. |
| Context windowmaximum listed tokens | DeepSeek V3.2 (Thinking)128K | Mistral Large 3128K | Listed context windows are equal. |
Benchmark Deep Dive
Agentic4 benchmarks
Coding3 benchmarks
Reasoning2 benchmarks
Knowledge6 benchmarks
| Benchmark | DeepSeek V3.2 (Thinking) | Mistral Large 3 | Result |
|---|---|---|---|
| Artificial Analysis Intelligence IndexSource | — | 15.9% | Not comparable |
| AA-GPQA DiamondSource | — | 68.0% | Not comparable |
| AA-HLESource | — | 4.1% | Not comparable |
| AA-Omniscience IndexSource | — | -39.4% | Not comparable |
| AA-Omniscience AccuracySource | — | 24.1% | Not comparable |
| AA-Omniscience Hallucination RateSource | — | 83.7% | Not comparable |
Multimodal2 benchmarks
Inst. Following1 benchmarks
| Benchmark | DeepSeek V3.2 (Thinking) | Mistral Large 3 | Result |
|---|---|---|---|
| AA-IFBenchSource | — | 36.2% | Not comparable |
Frequently Asked Questions (3)
Can I compare DeepSeek V3.2 (Thinking) and Mistral Large 3 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 DeepSeek V3.2 (Thinking) and Mistral Large 3 today?
DeepSeek V3.2 (Thinking): $0.55 input / $2.19 output per 1M tokens Mistral Large 3: $0.50 input / $1.50 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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