Model comparison
DeepSeek V4.1 Flash vs Devstral Small 2505
DeepSeek V4.1 Flash is the stronger model overall, scoring 52.8 to 34.3 on the Noometry Index. Devstral Small 2505 costs 1.7× less per token, which makes it the better buy when DeepSeek V4.1 Flash's lead doesn't matter for your workload.
Last verified . 2 shared benchmarks.
DeepSeek
Mistral AISummary
- They share 2 benchmarks with published results for both. DeepSeek V4.1 Flash scores higher in 2 categories and Devstral Small 2505 in 0 categories; 2 gaps are clear of the uncertainty.
- The widest gap is in reasoning, where DeepSeek V4.1 Flash leads 50.2 to 19.7.
- The biggest single-benchmark swing is SciCode: 51.9% for DeepSeek V4.1 Flash and 28.8% for Devstral Small 2505.
- Devstral Small 2505 is cheaper at $0.10 / $0.30 per million input/output tokens, against $0.15 / $0.60 for DeepSeek V4.1 Flash.
- DeepSeek V4.1 Flash accepts more context: 1M tokens versus 128K.
Side by side
| DeepSeek V4.1 Flash | Devstral Small 2505 | |
|---|---|---|
| Provider | DeepSeek | Mistral AI |
| Noometry Index | 52.8 | 34.3 |
| Released | 2026-09-09 | 2025-05-07 |
| Weights | Open | Open |
| Context window | 1M | 128K |
| Max output | 393K | 128K |
| Input $ / M tokens | $0.15 | $0.10 |
| Output $ / M tokens | $0.60 | $0.30 |
| Results tracked | 37 | 4 |
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Category by category
Coding DeepSeek V4.1 Flash leads
DeepSeek V4.1 Flash: 52.9 (#32), Devstral Small 2505: 38.9 (#166)
| Benchmark | DeepSeek V4.1 Flash | Devstral Small 2505 |
|---|---|---|
| SciCode | 51.9% | 28.8% |
| SWE-bench Verified (bash only) | — | 56.4% |
| LMArena WebDev | 1619 | — |
| LMArena Coding | 1506 | — |
| ALE-Bench | 1,092 | — |
Agentic & Tool Use Not comparable
DeepSeek V4.1 Flash: 31.2 (#69), Devstral Small 2505: —
| Benchmark | DeepSeek V4.1 Flash | Devstral Small 2505 |
|---|---|---|
| APEX-Agents | 39.5% | — |
| GDP.pdf | 19.8% | — |
Reasoning DeepSeek V4.1 Flash leads
DeepSeek V4.1 Flash: 50.2 (#36), Devstral Small 2505: 19.7 (#252)
| Benchmark | DeepSeek V4.1 Flash | Devstral Small 2505 |
|---|---|---|
| CritPt | 14.3% | 0% |
| Kagi LLM Benchmark | — | 37.7% |
| NYT Connections (extended) | 89.6% | — |
| LMArena Hard Prompts | 1483 | — |
| Mystery Game Puzzles | 43% | — |
| DTBench | 89.9% | — |
| LMCA | 47% | — |
| Surface Evolver Bench | 46.3% | — |
| Epoch Capabilities Index | 154.9 | — |
Math Not comparable
DeepSeek V4.1 Flash: 66.7 (#25), Devstral Small 2505: —
| Benchmark | DeepSeek V4.1 Flash | Devstral Small 2505 |
|---|---|---|
| FrontierMath (Tiers 1-3) | 67.4% | — |
| FrontierMath Tier 4 | 26.8% | — |
| OTIS Mock AIME 2024-2025 | 98.3% | — |
| ProofBench | 54% | — |
| LMArena Math | 1477 | — |
Knowledge Not comparable
DeepSeek V4.1 Flash: 57.9 (#38), Devstral Small 2505: —
| Benchmark | DeepSeek V4.1 Flash | Devstral Small 2505 |
|---|---|---|
| GPQA Diamond | 89.8% | — |
| LMArena Expert | 1506 | — |
Multimodal Not comparable
DeepSeek V4.1 Flash: 39.1 (#61), Devstral Small 2505: —
| Benchmark | DeepSeek V4.1 Flash | Devstral Small 2505 |
|---|---|---|
| LMArena Vision | 1277 | — |
| Furniture Assembly | 34.2% | — |
Multilingual Not comparable
DeepSeek V4.1 Flash: 55.0 (#35), Devstral Small 2505: —
| Benchmark | DeepSeek V4.1 Flash | Devstral Small 2505 |
|---|---|---|
| LMArena Non-English | 1448 | — |
| LMArena Chinese | 1497 | — |
| LMArena French | 1452 | — |
| LMArena German | 1484 | — |
| LMArena Japanese | 1412 | — |
| LMArena Korean | 1452 | — |
| LMArena Russian | 1471 | — |
| LMArena Spanish | 1459 | — |
Instruction Following Not comparable
DeepSeek V4.1 Flash: 77.3 (#26), Devstral Small 2505: —
| Benchmark | DeepSeek V4.1 Flash | Devstral Small 2505 |
|---|---|---|
| LMArena Instruction Following | 1474 | — |
Long Context Not comparable
DeepSeek V4.1 Flash: 45.2 (#47), Devstral Small 2505: —
| Benchmark | DeepSeek V4.1 Flash | Devstral Small 2505 |
|---|---|---|
| LMArena Longer Query | 1475 | — |
Writing & Preference Not comparable
DeepSeek V4.1 Flash: 65.4 (#48), Devstral Small 2505: —
| Benchmark | DeepSeek V4.1 Flash | Devstral Small 2505 |
|---|---|---|
| LMArena Text | 1462 | — |
| LMArena Creative Writing | 1435 | — |
| EQ-Bench Creative Writing | 1540 | — |
| LMArena Multi-Turn | 1457 | — |
Frequently asked questions
Is DeepSeek V4.1 Flash better than Devstral Small 2505?
DeepSeek V4.1 Flash is the stronger model overall, scoring 52.8 to 34.3 on the Noometry Index. Devstral Small 2505 costs 1.7× less per token, which makes it the better buy when DeepSeek V4.1 Flash's lead doesn't matter for your workload.
Which is cheaper, DeepSeek V4.1 Flash or Devstral Small 2505?
Devstral Small 2505 is cheaper. It lists at $0.10 per million input tokens and $0.30 per million output tokens; DeepSeek V4.1 Flash lists at $0.15 and $0.60.
Is DeepSeek V4.1 Flash or Devstral Small 2505 better for coding?
DeepSeek V4.1 Flash scores higher on coding benchmarks: 52.9 versus 38.9 in the Noometry coding category.
Which has the bigger context window?
DeepSeek V4.1 Flash does, with 1M tokens against 128K.
How many benchmarks do DeepSeek V4.1 Flash and Devstral Small 2505 share?
2 benchmarks have published results for both models. DeepSeek V4.1 Flash has 37 scored results on Noometry and Devstral Small 2505 has 4.