Model comparison
GPT-6 Luna vs Ministral 3B
GPT-6 Luna is the stronger model overall, scoring 53.3 to 26.2 on the Noometry Index. Ministral 3B costs 2.0× less per token, which makes it the better buy when GPT-6 Luna's lead doesn't matter for your workload.
Last verified . 4 shared benchmarks.
Mistral AISummary
- They share 4 benchmarks with published results for both. GPT-6 Luna scores higher in 3 categories and Ministral 3B in 0 categories; 3 gaps are clear of the uncertainty.
- The widest gap is in math, where GPT-6 Luna leads 76.1 to 26.6.
- The biggest single-benchmark swing is GPQA Diamond: 90.5% for GPT-6 Luna and 25.3% for Ministral 3B.
- Ministral 3B is cheaper at $0.10 / $0.10 per million input/output tokens, against $0.10 / $0.50 for GPT-6 Luna.
- GPT-6 Luna accepts more context: 1.05M tokens versus 131K.
- Ministral 3B has downloadable open weights; the other is API-only.
Side by side
| GPT-6 Luna | Ministral 3B | |
|---|---|---|
| Provider | OpenAI | Mistral AI |
| Noometry Index | 53.3 | 26.2 |
| Released | 2026-09-22 | 2024-10-01 |
| Weights | Proprietary | Open |
| Context window | 1.05M | 131K |
| Max output | 128K | 262K |
| Input $ / M tokens | $0.10 | $0.10 |
| Output $ / M tokens | $0.50 | $0.10 |
| Results tracked | 42 | 6 |
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Category by category
Coding Not comparable
GPT-6 Luna: 55.5 (#25), Ministral 3B: —
| Benchmark | GPT-6 Luna | Ministral 3B |
|---|---|---|
| DeepSWE | 66.6% | — |
| FrontierCode | 42.4% | — |
| LMArena WebDev | 1581 | — |
| SciCode | 54.6% | — |
| LMArena Coding | 1439 | — |
| ALE-Bench | 1,577 | — |
Agentic & Tool Use Not comparable
GPT-6 Luna: 33.3 (#54), Ministral 3B: —
| Benchmark | GPT-6 Luna | Ministral 3B |
|---|---|---|
| APEX-Agents | 44.3% | — |
| GDP.pdf | 23% | — |
Reasoning GPT-6 Luna leads
GPT-6 Luna: 48.2 (#41), Ministral 3B: 18.4 (#282)
| Benchmark | GPT-6 Luna | Ministral 3B |
|---|---|---|
| DTBench | 90.1% | 51.7% |
| LMCA | 44.5% | 5.5% |
| Epoch Capabilities Index | 156.28 | 118.1 |
| ARC-AGI-2 | 59.3% | — |
| NYT Connections (extended) | 68.7% | — |
| ARC-AGI-1 | 86.7% | — |
| CritPt | 19.4% | — |
| Chess Puzzles | 31% | — |
| LMArena Hard Prompts | 1411 | — |
| Mystery Game Puzzles | 7% | — |
Math GPT-6 Luna leads
GPT-6 Luna: 76.1 (#15), Ministral 3B: 26.6 (#258)
| Benchmark | GPT-6 Luna | Ministral 3B |
|---|---|---|
| FrontierMath (Tiers 1-3) | 78.9% | — |
| FrontierMath Tier 4 | 56.1% | — |
| OTIS Mock AIME 2024-2025 | 98.9% | — |
| ProofBench | 64% | — |
| LMArena Math | 1416 | — |
| MATH Level 5 | — | 14.4% |
Knowledge GPT-6 Luna leads
GPT-6 Luna: 57.0 (#41), Ministral 3B: 10.4 (#302)
| Benchmark | GPT-6 Luna | Ministral 3B |
|---|---|---|
| GPQA Diamond | 90.5% | 25.3% |
| SimpleQA Verified | 41.4% | — |
| Vectara Hallucination Rate | — | 7.3% |
| LMArena Expert | 1444 | — |
Multimodal Not comparable
GPT-6 Luna: 42.4 (#30), Ministral 3B: —
| Benchmark | GPT-6 Luna | Ministral 3B |
|---|---|---|
| LMArena Vision | 1217 | — |
| Blueprint-Bench 2 | 31.2% | — |
| Furniture Assembly | 44.2% | — |
Multilingual Not comparable
GPT-6 Luna: 50.5 (#117), Ministral 3B: —
| Benchmark | GPT-6 Luna | Ministral 3B |
|---|---|---|
| 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
GPT-6 Luna: 74.3 (#99), Ministral 3B: —
| Benchmark | GPT-6 Luna | Ministral 3B |
|---|---|---|
| LMArena Instruction Following | 1409 | — |
Long Context Not comparable
GPT-6 Luna: 43.0 (#111), Ministral 3B: —
| Benchmark | GPT-6 Luna | Ministral 3B |
|---|---|---|
| LMArena Longer Query | 1409 | — |
Writing & Preference Not comparable
GPT-6 Luna: 58.3 (#119), Ministral 3B: —
| Benchmark | GPT-6 Luna | Ministral 3B |
|---|---|---|
| LMArena Text | 1391 | — |
| LMArena Creative Writing | 1363 | — |
| LMArena Multi-Turn | 1396 | — |
Frequently asked questions
Is GPT-6 Luna better than Ministral 3B?
GPT-6 Luna is the stronger model overall, scoring 53.3 to 26.2 on the Noometry Index. Ministral 3B costs 2.0× 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 Ministral 3B?
Ministral 3B is cheaper. It lists at $0.10 per million input tokens and $0.10 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 131K.
How many benchmarks do GPT-6 Luna and Ministral 3B share?
4 benchmarks have published results for both models. GPT-6 Luna has 42 scored results on Noometry and Ministral 3B has 6.