Model comparison
DeepSeek V4 Pro vs Ministral 3 8B 2512 (batch)
DeepSeek V4 Pro has enough public results to be ranked (#28); Ministral 3 8B 2512 (batch) does not yet, so treat this comparison as directional.
Last verified . 1 shared benchmarks.
DeepSeek
Mistral AISummary
- They share 1 benchmark with published results for both. DeepSeek V4 Pro scores higher in 1 category and Ministral 3 8B 2512 (batch) in 0 categories; one gap is clear of the uncertainty.
- The widest gap is in knowledge, where DeepSeek V4 Pro leads 59.5 to 26.6.
- The biggest single-benchmark swing is Vectara Hallucination Rate: 8.6% for DeepSeek V4 Pro and 21.7% for Ministral 3 8B 2512 (batch).
- Ministral 3 8B 2512 (batch) is cheaper at $0.075 / $0.075 per million input/output tokens, against $0.43 / $0.87 for DeepSeek V4 Pro.
- DeepSeek V4 Pro accepts more context: 1M tokens versus 128K.
Side by side
| DeepSeek V4 Pro | Ministral 3 8B 2512 (batch) | |
|---|---|---|
| Provider | DeepSeek | Mistral AI |
| Noometry Index | 54.2 | 32.3 |
| Released | 2026-04-24 | 2025-12-02 |
| Weights | Open | Open |
| Context window | 1M | 128K |
| Max output | 393K | 4K |
| Input $ / M tokens | $0.43 | $0.075 |
| Output $ / M tokens | $0.87 | $0.075 |
| Results tracked | 48 | 1 |
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Category by category
Coding Not comparable
DeepSeek V4 Pro: 52.2 (#31), Ministral 3 8B 2512 (batch): —
| Benchmark | DeepSeek V4 Pro | Ministral 3 8B 2512 (batch) |
|---|---|---|
| SWE-bench Verified | 77.6% | — |
| FrontierCode | 28.6% | — |
| LMArena WebDev | 1582 | — |
| SciCode | 51% | — |
| WeirdML | 66.2% | — |
| LMArena Coding | 1470 | — |
| ALE-Bench | 1,403 | — |
Agentic & Tool Use Not comparable
DeepSeek V4 Pro: 32.7 (#54), Ministral 3 8B 2512 (batch): —
| Benchmark | DeepSeek V4 Pro | Ministral 3 8B 2512 (batch) |
|---|---|---|
| APEX-Agents | 47.3% | — |
| Vending-Bench 2 | 3,285 | — |
Reasoning Not comparable
DeepSeek V4 Pro: 56.4 (#22), Ministral 3 8B 2512 (batch): —
| Benchmark | DeepSeek V4 Pro | Ministral 3 8B 2512 (batch) |
|---|---|---|
| ARC-AGI-2 | 61.3% | — |
| Kagi LLM Benchmark | 53.5% | — |
| NYT Connections (extended) | 91.3% | — |
| ARC-AGI-1 | 90.5% | — |
| CritPt | 18% | — |
| Chess Puzzles | 47% | — |
| LMArena Hard Prompts | 1461 | — |
| Mystery Game Puzzles | 43% | — |
| DTBench | 93.9% | — |
| LMCA | 45.5% | — |
| Surface Evolver Bench | 40% | — |
| Epoch Capabilities Index | 155.39 | — |
| ForecastBench | 56.1 | — |
Math Not comparable
DeepSeek V4 Pro: 64.6 (#24), Ministral 3 8B 2512 (batch): —
| Benchmark | DeepSeek V4 Pro | Ministral 3 8B 2512 (batch) |
|---|---|---|
| FrontierMath (Tiers 1-3) | 64.6% | — |
| FrontierMath Tier 4 | 26.8% | — |
| MathArena Final-Answer Competitions | 76.6% | — |
| OTIS Mock AIME 2024-2025 | 98.6% | — |
| ProofBench | 50% | — |
| LMArena Math | 1455 | — |
Knowledge DeepSeek V4 Pro leads
DeepSeek V4 Pro: 59.5 (#28), Ministral 3 8B 2512 (batch): 26.6
| Benchmark | DeepSeek V4 Pro | Ministral 3 8B 2512 (batch) |
|---|---|---|
| Vectara Hallucination Rate | 8.6% | 21.7% |
| GPQA Diamond | 91.7% | — |
| SimpleQA Verified | 52.9% | — |
| LMArena Expert | 1463 | — |
Multilingual Not comparable
DeepSeek V4 Pro: 54.5 (#44), Ministral 3 8B 2512 (batch): —
| Benchmark | DeepSeek V4 Pro | Ministral 3 8B 2512 (batch) |
|---|---|---|
| LMArena Non-English | 1438 | — |
| LMArena Chinese | 1486 | — |
| LMArena French | 1473 | — |
| LMArena German | 1458 | — |
| LMArena Japanese | 1448 | — |
| LMArena Korean | 1452 | — |
| LMArena Russian | 1452 | — |
| LMArena Spanish | 1457 | — |
Instruction Following Not comparable
DeepSeek V4 Pro: 76.3 (#44), Ministral 3 8B 2512 (batch): —
| Benchmark | DeepSeek V4 Pro | Ministral 3 8B 2512 (batch) |
|---|---|---|
| LMArena Instruction Following | 1448 | — |
Long Context Not comparable
DeepSeek V4 Pro: 45.0 (#49), Ministral 3 8B 2512 (batch): —
| Benchmark | DeepSeek V4 Pro | Ministral 3 8B 2512 (batch) |
|---|---|---|
| CL-bench Life | 13.5% | — |
| LMArena Longer Query | 1459 | — |
Writing & Preference Not comparable
DeepSeek V4 Pro: 65.6 (#45), Ministral 3 8B 2512 (batch): —
| Benchmark | DeepSeek V4 Pro | Ministral 3 8B 2512 (batch) |
|---|---|---|
| LMArena Text | 1451 | — |
| LMArena Creative Writing | 1446 | — |
| EQ-Bench Creative Writing | 1553 | — |
| EQ-Bench 4 | 1166 | — |
| LMArena Multi-Turn | 1467 | — |
Frequently asked questions
Is DeepSeek V4 Pro better than Ministral 3 8B 2512 (batch)?
DeepSeek V4 Pro has enough public results to be ranked (#28); Ministral 3 8B 2512 (batch) does not yet, so treat this comparison as directional.
Which is cheaper, DeepSeek V4 Pro or Ministral 3 8B 2512 (batch)?
Ministral 3 8B 2512 (batch) is cheaper. It lists at $0.075 per million input tokens and $0.075 per million output tokens; DeepSeek V4 Pro lists at $0.43 and $0.87.
Which has the bigger context window?
DeepSeek V4 Pro does, with 1M tokens against 128K.
How many benchmarks do DeepSeek V4 Pro and Ministral 3 8B 2512 (batch) share?
1 benchmark has published results for both models. DeepSeek V4 Pro has 48 scored results on Noometry and Ministral 3 8B 2512 (batch) has 1.