Model comparison
GPT-6 Luna vs Mistral Small 3.2
GPT-6 Luna is the stronger model overall, scoring 45.1 to 30.8 on the Noometry Index. Mistral Small 3.2 costs 1.5× less per token, which makes it the better buy when GPT-6 Luna's lead doesn't matter for your workload.
Last verified . 0 shared benchmarks.
Mistral AISummary
- The widest gap is in reasoning, where GPT-6 Luna leads 31.7 to 17.5.
- Mistral Small 3.2 is cheaper at $0.0938 / $0.25 per million input/output tokens, against $0.10 / $0.50 for GPT-6 Luna.
- GPT-6 Luna accepts more context: 1.05M tokens versus 256K.
- Mistral Small 3.2 has downloadable open weights; the other is API-only.
Side by side
| GPT-6 Luna | Mistral Small 3.2 | |
|---|---|---|
| Provider | OpenAI | Mistral AI |
| Noometry Index | 45.1 | 30.8 |
| Released | 2026-09-22 | 2025-06-20 |
| Weights | Proprietary | Open |
| Context window | 1.05M | 256K |
| Max output | 128K | 16K |
| Input $ / M tokens | $0.10 | $0.0938 |
| Output $ / M tokens | $0.50 | $0.25 |
| Results tracked | 18 | 6 |
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Category by category
Coding Not comparable
GPT-6 Luna: 54.7 (#24), Mistral Small 3.2: —
| Benchmark | GPT-6 Luna | Mistral Small 3.2 |
|---|---|---|
| DeepSWE | 66.6% | — |
| FrontierCode | 42.4% | — |
| LMArena WebDev | 1583 | — |
| LMArena Coding | 1448 | — |
Reasoning GPT-6 Luna leads
GPT-6 Luna: 31.7 (#68), Mistral Small 3.2: 17.5 (#282)
| Benchmark | GPT-6 Luna | Mistral Small 3.2 |
|---|---|---|
| Kagi LLM Benchmark | — | 40.4% |
| NYT Connections (extended) | 68.7% | — |
| Chess Puzzles | — | 1% |
| LMArena Hard Prompts | 1415 | — |
| Epoch Capabilities Index | — | 131.73 |
Math GPT-6 Luna leads
GPT-6 Luna: 35.6 (#140), Mistral Small 3.2: 24.9 (#251)
| Benchmark | GPT-6 Luna | Mistral Small 3.2 |
|---|---|---|
| OTIS Mock AIME 2024-2025 | — | 30.3% |
| LMArena Math | 1396 | — |
Knowledge GPT-6 Luna leads
GPT-6 Luna: 40.1 (#110), Mistral Small 3.2: 26.8 (#249)
| Benchmark | GPT-6 Luna | Mistral Small 3.2 |
|---|---|---|
| GPQA Diamond | — | 49.1% |
| LMArena Expert | 1458 | — |
Multimodal Not comparable
GPT-6 Luna: 42.0 (#27), Mistral Small 3.2: —
| Benchmark | GPT-6 Luna | Mistral Small 3.2 |
|---|---|---|
| Furniture Assembly | 44.2% | — |
Multilingual Not comparable
GPT-6 Luna: 51.0 (#111), Mistral Small 3.2: —
| Benchmark | GPT-6 Luna | Mistral Small 3.2 |
|---|---|---|
| LMArena Non-English | 1390 | — |
| LMArena Chinese | 1425 | — |
| LMArena Russian | 1392 | — |
| LMArena Spanish | 1416 | — |
Instruction Following Not comparable
GPT-6 Luna: 74.7 (#85), Mistral Small 3.2: —
| Benchmark | GPT-6 Luna | Mistral Small 3.2 |
|---|---|---|
| LMArena Instruction Following | 1414 | — |
Long Context Not comparable
GPT-6 Luna: 43.3 (#95), Mistral Small 3.2: —
| Benchmark | GPT-6 Luna | Mistral Small 3.2 |
|---|---|---|
| LMArena Longer Query | 1417 | — |
Writing & Preference GPT-6 Luna leads
GPT-6 Luna: 58.4 (#115), Mistral Small 3.2: 45.1 (#219)
| Benchmark | GPT-6 Luna | Mistral Small 3.2 |
|---|---|---|
| LMArena Text | 1392 | — |
| LMArena Creative Writing | 1357 | — |
| EQ-Bench Creative Writing | — | 1255 |
| LMArena Multi-Turn | 1400 | — |
Frequently asked questions
Is GPT-6 Luna better than Mistral Small 3.2?
GPT-6 Luna is the stronger model overall, scoring 45.1 to 30.8 on the Noometry Index. Mistral Small 3.2 costs 1.5× less per token, which makes it the better buy when GPT-6 Luna's lead doesn't matter for your workload.
Which is cheaper, GPT-6 Luna or Mistral Small 3.2?
Mistral Small 3.2 is cheaper. It lists at $0.0938 per million input tokens and $0.25 per million output tokens; GPT-6 Luna lists at $0.10 and $0.50.
Which has the bigger context window?
GPT-6 Luna does, with 1.05M tokens against 256K.
How many benchmarks do GPT-6 Luna and Mistral Small 3.2 share?
0 benchmarks have published results for both models. GPT-6 Luna has 18 scored results on Noometry and Mistral Small 3.2 has 6.