Model comparison
GPT-5.2 Codex vs Mistral 7B
GPT-5.2 Codex is the stronger model overall, scoring 42.6 to 23.0 on the Noometry Index. Mistral 7B costs 19× less per token, which makes it the better buy when GPT-5.2 Codex's lead doesn't matter for your workload.
Last verified . 0 shared benchmarks.
Mistral AISummary
- The widest gap is in coding, where GPT-5.2 Codex leads 45.5 to 26.4.
- Mistral 7B is cheaper at $0.25 / $0.25 per million input/output tokens, against $1.75 / $14 for GPT-5.2 Codex.
- GPT-5.2 Codex accepts more context: 400K tokens versus 8K.
- Mistral 7B has downloadable open weights; the other is API-only.
Side by side
| GPT-5.2 Codex | Mistral 7B | |
|---|---|---|
| Provider | OpenAI | Mistral AI |
| Noometry Index | 42.6 | 23.0 |
| Released | 2025-12-18 | 2023-09-27 |
| Weights | Proprietary | Open |
| Context window | 400K | 8K |
| Max output | 128K | 8K |
| Input $ / M tokens | $1.75 | $0.25 |
| Output $ / M tokens | $14 | $0.25 |
| Results tracked | 5 | 37 |
Sponsored placements are available on pages like this one. Advertise on Noometry
Category by category
Coding GPT-5.2 Codex leads
GPT-5.2 Codex: 45.5 (#71), Mistral 7B: 26.4 (#326)
| Benchmark | GPT-5.2 Codex | Mistral 7B |
|---|---|---|
| SWE-bench Verified (bash only) | 72.8% | — |
| LMArena WebDev | 1339 | — |
| SWE-bench Multilingual | 66.3% | — |
| BigCodeBench Instruct | — | 19.5% |
| LMArena Coding | — | 1082 |
| BigCodeBench Complete | — | 27.3% |
| ALE-Bench | 1,300 | — |
| HumanEval+ | — | 36% |
| MBPP+ | — | 42.1% |
Agentic & Tool Use Not comparable
GPT-5.2 Codex: 41.0 (#22), Mistral 7B: —
| Benchmark | GPT-5.2 Codex | Mistral 7B |
|---|---|---|
| Terminal-Bench | 66.5% | — |
Reasoning Not comparable
GPT-5.2 Codex: —, Mistral 7B: 13.1 (#336)
| Benchmark | GPT-5.2 Codex | Mistral 7B |
|---|---|---|
| Chess Puzzles | — | 0% |
| LMArena Hard Prompts | — | 1067 |
| DTBench | — | 42.5% |
| Adversarial NLI | — | 47.1% |
| BIG-Bench Hard | — | 56.1% |
| Epoch Capabilities Index | — | 112.21 |
| HellaSwag | — | 81% |
| PIQA | — | 83% |
| WinoGrande | — | 75.3% |
Math Not comparable
GPT-5.2 Codex: —, Mistral 7B: 8.1 (#325)
| Benchmark | GPT-5.2 Codex | Mistral 7B |
|---|---|---|
| OTIS Mock AIME 2024-2025 | — | 0.3% |
| LMArena Math | — | 1085 |
| MATH Level 5 | — | 3.7% |
| GSM8K | — | 54.4% |
Knowledge Not comparable
GPT-5.2 Codex: —, Mistral 7B: 7.4 (#311)
| Benchmark | GPT-5.2 Codex | Mistral 7B |
|---|---|---|
| GPQA Diamond | — | 15.2% |
| LMArena Expert | — | 1036 |
| ARC (AI2) Challenge | — | 78.6% |
| BoolQ | — | 87.4% |
| MMLU | — | 62.5% |
| OpenBookQA | — | 79.8% |
| TriviaQA | — | 75.2% |
Multilingual Not comparable
GPT-5.2 Codex: —, Mistral 7B: 25.8 (#283)
| Benchmark | GPT-5.2 Codex | Mistral 7B |
|---|---|---|
| LMArena Non-English | — | 1012 |
| LMArena Chinese | — | 1009 |
| LMArena French | — | 1037 |
| LMArena German | — | 987 |
| LMArena Japanese | — | 878 |
| LMArena Russian | — | 1018 |
| LMArena Spanish | — | 1026 |
Instruction Following Not comparable
GPT-5.2 Codex: —, Mistral 7B: 54.2 (#280)
| Benchmark | GPT-5.2 Codex | Mistral 7B |
|---|---|---|
| LMArena Instruction Following | — | 1060 |
Long Context Not comparable
GPT-5.2 Codex: —, Mistral 7B: 32.2 (#271)
| Benchmark | GPT-5.2 Codex | Mistral 7B |
|---|---|---|
| LMArena Longer Query | — | 1060 |
Writing & Preference Not comparable
GPT-5.2 Codex: —, Mistral 7B: 30.7 (#286)
| Benchmark | GPT-5.2 Codex | Mistral 7B |
|---|---|---|
| LMArena Text | — | 1090 |
| LMArena Creative Writing | — | 1068 |
| LMArena Multi-Turn | — | 1062 |
Frequently asked questions
Is GPT-5.2 Codex better than Mistral 7B?
GPT-5.2 Codex is the stronger model overall, scoring 42.6 to 23.0 on the Noometry Index. Mistral 7B costs 19× less per token, which makes it the better buy when GPT-5.2 Codex's lead doesn't matter for your workload.
Which is cheaper, GPT-5.2 Codex or Mistral 7B?
Mistral 7B is cheaper. It lists at $0.25 per million input tokens and $0.25 per million output tokens; GPT-5.2 Codex lists at $1.75 and $14.
Is GPT-5.2 Codex or Mistral 7B better for coding?
GPT-5.2 Codex scores higher on coding benchmarks: 45.5 versus 26.4 in the Noometry coding category.
Which has the bigger context window?
GPT-5.2 Codex does, with 400K tokens against 8K.
How many benchmarks do GPT-5.2 Codex and Mistral 7B share?
0 benchmarks have published results for both models. GPT-5.2 Codex has 5 scored results on Noometry and Mistral 7B has 37.