Model comparison
Devstral Small 2505 vs GPT-6 Luna
GPT-6 Luna is the stronger model overall, scoring 53.3 to 34.3 on the Noometry Index.
Last verified . 2 shared benchmarks.
Mistral AISummary
- They share 2 benchmarks with published results for both. Devstral Small 2505 scores higher in 0 categories and GPT-6 Luna in 2 categories; 2 gaps are clear of the uncertainty.
- The widest gap is in reasoning, where GPT-6 Luna leads 48.2 to 19.7.
- The biggest single-benchmark swing is SciCode: 28.8% for Devstral Small 2505 and 54.6% for GPT-6 Luna.
- Devstral Small 2505 is cheaper at $0.10 / $0.30 per million input/output tokens, against $0.10 / $0.50 for GPT-6 Luna.
- GPT-6 Luna accepts more context: 1.05M tokens versus 128K.
- Devstral Small 2505 has downloadable open weights; the other is API-only.
Side by side
| Devstral Small 2505 | GPT-6 Luna | |
|---|---|---|
| Provider | Mistral AI | OpenAI |
| Noometry Index | 34.3 | 53.3 |
| Released | 2025-05-07 | 2026-09-22 |
| Weights | Open | Proprietary |
| Context window | 128K | 1.05M |
| Max output | 128K | 128K |
| Input $ / M tokens | $0.10 | $0.10 |
| Output $ / M tokens | $0.30 | $0.50 |
| Results tracked | 4 | 42 |
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Category by category
Coding GPT-6 Luna leads
Devstral Small 2505: 38.9 (#166), GPT-6 Luna: 55.5 (#25)
| Benchmark | Devstral Small 2505 | GPT-6 Luna |
|---|---|---|
| SciCode | 28.8% | 54.6% |
| DeepSWE | — | 66.6% |
| FrontierCode | — | 42.4% |
| SWE-bench Verified (bash only) | 56.4% | — |
| LMArena WebDev | — | 1581 |
| LMArena Coding | — | 1439 |
| ALE-Bench | — | 1,577 |
Agentic & Tool Use Not comparable
Devstral Small 2505: —, GPT-6 Luna: 33.3 (#54)
| Benchmark | Devstral Small 2505 | GPT-6 Luna |
|---|---|---|
| APEX-Agents | — | 44.3% |
| GDP.pdf | — | 23% |
Reasoning GPT-6 Luna leads
Devstral Small 2505: 19.7 (#252), GPT-6 Luna: 48.2 (#41)
| Benchmark | Devstral Small 2505 | GPT-6 Luna |
|---|---|---|
| CritPt | 0% | 19.4% |
| ARC-AGI-2 | — | 59.3% |
| Kagi LLM Benchmark | 37.7% | — |
| NYT Connections (extended) | — | 68.7% |
| ARC-AGI-1 | — | 86.7% |
| Chess Puzzles | — | 31% |
| LMArena Hard Prompts | — | 1411 |
| Mystery Game Puzzles | — | 7% |
| DTBench | — | 90.1% |
| LMCA | — | 44.5% |
| Epoch Capabilities Index | — | 156.28 |
Math Not comparable
Devstral Small 2505: —, GPT-6 Luna: 76.1 (#15)
| Benchmark | Devstral Small 2505 | GPT-6 Luna |
|---|---|---|
| FrontierMath (Tiers 1-3) | — | 78.9% |
| FrontierMath Tier 4 | — | 56.1% |
| OTIS Mock AIME 2024-2025 | — | 98.9% |
| ProofBench | — | 64% |
| LMArena Math | — | 1416 |
Knowledge Not comparable
Devstral Small 2505: —, GPT-6 Luna: 57.0 (#41)
| Benchmark | Devstral Small 2505 | GPT-6 Luna |
|---|---|---|
| GPQA Diamond | — | 90.5% |
| SimpleQA Verified | — | 41.4% |
| LMArena Expert | — | 1444 |
Multimodal Not comparable
Devstral Small 2505: —, GPT-6 Luna: 42.4 (#30)
| Benchmark | Devstral Small 2505 | GPT-6 Luna |
|---|---|---|
| LMArena Vision | — | 1217 |
| Blueprint-Bench 2 | — | 31.2% |
| Furniture Assembly | — | 44.2% |
Multilingual Not comparable
Devstral Small 2505: —, GPT-6 Luna: 50.5 (#117)
| Benchmark | Devstral Small 2505 | GPT-6 Luna |
|---|---|---|
| LMArena Non-English | — | 1386 |
| LMArena Chinese | — | 1433 |
| LMArena French | — | 1420 |
| LMArena German | — | 1369 |
| LMArena Japanese | — | 1369 |
| LMArena Korean | — | 1360 |
| LMArena Russian | — | 1394 |
| LMArena Spanish | — | 1393 |
Instruction Following Not comparable
Devstral Small 2505: —, GPT-6 Luna: 74.3 (#99)
| Benchmark | Devstral Small 2505 | GPT-6 Luna |
|---|---|---|
| LMArena Instruction Following | — | 1409 |
Long Context Not comparable
Devstral Small 2505: —, GPT-6 Luna: 43.0 (#111)
| Benchmark | Devstral Small 2505 | GPT-6 Luna |
|---|---|---|
| LMArena Longer Query | — | 1409 |
Writing & Preference Not comparable
Devstral Small 2505: —, GPT-6 Luna: 58.3 (#119)
| Benchmark | Devstral Small 2505 | GPT-6 Luna |
|---|---|---|
| LMArena Text | — | 1391 |
| LMArena Creative Writing | — | 1363 |
| LMArena Multi-Turn | — | 1396 |
Frequently asked questions
Is Devstral Small 2505 better than GPT-6 Luna?
GPT-6 Luna is the stronger model overall, scoring 53.3 to 34.3 on the Noometry Index.
Which is cheaper, Devstral Small 2505 or GPT-6 Luna?
Devstral Small 2505 is cheaper. It lists at $0.10 per million input tokens and $0.30 per million output tokens; GPT-6 Luna lists at $0.10 and $0.50.
Is Devstral Small 2505 or GPT-6 Luna better for coding?
GPT-6 Luna scores higher on coding benchmarks: 55.5 versus 38.9 in the Noometry coding category.
Which has the bigger context window?
GPT-6 Luna does, with 1.05M tokens against 128K.
How many benchmarks do Devstral Small 2505 and GPT-6 Luna share?
2 benchmarks have published results for both models. Devstral Small 2505 has 4 scored results on Noometry and GPT-6 Luna has 42.