Model comparison
GPT-5.3 Chat vs Mixtral 8x22B
GPT-5.3 Chat is the stronger model overall, scoring 42.8 to 27.1 on the Noometry Index. Mixtral 8x22B costs 1.6× less per token, which makes it the better buy when GPT-5.3 Chat's lead doesn't matter for your workload.
Last verified . 17 shared benchmarks.
Mistral AISummary
- They share 17 benchmarks with published results for both. GPT-5.3 Chat scores higher in 8 categories and Mixtral 8x22B in 0 categories; 8 gaps are clear of the uncertainty.
- The widest gap is in writing & preference, where GPT-5.3 Chat leads 63.1 to 36.9.
- Mixtral 8x22B is cheaper at $2 / $6 per million input/output tokens, against $1.75 / $14 for GPT-5.3 Chat.
- GPT-5.3 Chat accepts more context: 128K tokens versus 64K.
- Mixtral 8x22B has downloadable open weights; the other is API-only.
Side by side
| GPT-5.3 Chat | Mixtral 8x22B | |
|---|---|---|
| Provider | OpenAI | Mistral AI |
| Noometry Index | 42.8 | 27.1 |
| Released | 2026-03-03 | 2024-04-17 |
| Weights | Proprietary | Open |
| Context window | 128K | 64K |
| Max output | 16K | 64K |
| Input $ / M tokens | $1.75 | $2 |
| Output $ / M tokens | $14 | $6 |
| Results tracked | 18 | 34 |
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Category by category
Coding GPT-5.3 Chat leads
GPT-5.3 Chat: 41.4 (#124), Mixtral 8x22B: 24.2 (#329)
| Benchmark | GPT-5.3 Chat | Mixtral 8x22B |
|---|---|---|
| LMArena Coding | 1408 | 1166 |
| WeirdML | — | 3.2% |
| BigCodeBench Instruct | — | 40.6% |
| BigCodeBench Complete | — | 50.2% |
| HumanEval+ | — | 72% |
| MBPP+ | — | 64.3% |
Agentic & Tool Use Not comparable
GPT-5.3 Chat: —, Mixtral 8x22B: 23.1 (#127)
| Benchmark | GPT-5.3 Chat | Mixtral 8x22B |
|---|---|---|
| Cybench | — | 7.5% |
Reasoning GPT-5.3 Chat leads
GPT-5.3 Chat: 28.5 (#102), Mixtral 8x22B: 19.9 (#248)
| Benchmark | GPT-5.3 Chat | Mixtral 8x22B |
|---|---|---|
| LMArena Hard Prompts | 1399 | 1150 |
| DTBench | — | 55.1% |
| Epoch Capabilities Index | — | 122.03 |
| ForecastBench | — | 56.3 |
Math GPT-5.3 Chat leads
GPT-5.3 Chat: 38.2 (#142), Mixtral 8x22B: 22.9 (#275)
| Benchmark | GPT-5.3 Chat | Mixtral 8x22B |
|---|---|---|
| LMArena Math | 1389 | 1184 |
| Omni-MATH | — | 16.3% |
| MATH Level 5 | — | 24.2% |
Knowledge GPT-5.3 Chat leads
GPT-5.3 Chat: 38.8 (#140), Mixtral 8x22B: 15.1 (#293)
| Benchmark | GPT-5.3 Chat | Mixtral 8x22B |
|---|---|---|
| LMArena Expert | 1397 | 1113 |
| GPQA Diamond | — | 34.1% |
| MMLU-Pro | — | 46% |
| GPQA (HELM) | — | 33.4% |
| MMLU | — | 77.8% |
Multilingual GPT-5.3 Chat leads
GPT-5.3 Chat: 50.3 (#124), Mixtral 8x22B: 32.8 (#255)
| Benchmark | GPT-5.3 Chat | Mixtral 8x22B |
|---|---|---|
| LMArena Non-English | 1382 | 1128 |
| LMArena Chinese | 1432 | 1116 |
| LMArena French | 1397 | 1166 |
| LMArena German | 1384 | 1141 |
| LMArena Japanese | 1352 | 1037 |
| LMArena Korean | 1346 | 1057 |
| LMArena Russian | 1400 | 1158 |
| LMArena Spanish | 1371 | 1151 |
Instruction Following GPT-5.3 Chat leads
GPT-5.3 Chat: 72.8 (#129), Mixtral 8x22B: 57.7 (#266)
| Benchmark | GPT-5.3 Chat | Mixtral 8x22B |
|---|---|---|
| LMArena Instruction Following | 1378 | 1147 |
| IFEval | — | 72.4% |
Long Context GPT-5.3 Chat leads
GPT-5.3 Chat: 42.6 (#120), Mixtral 8x22B: 34.7 (#247)
| Benchmark | GPT-5.3 Chat | Mixtral 8x22B |
|---|---|---|
| LMArena Longer Query | 1396 | 1144 |
Writing & Preference GPT-5.3 Chat leads
GPT-5.3 Chat: 63.1 (#68), Mixtral 8x22B: 36.9 (#262)
| Benchmark | GPT-5.3 Chat | Mixtral 8x22B |
|---|---|---|
| LMArena Text | 1389 | 1162 |
| LMArena Creative Writing | 1355 | 1141 |
| LMArena Multi-Turn | 1412 | 1130 |
| EQ-Bench Creative Writing | 1690 | — |
| WildBench | — | 71.1% |
Frequently asked questions
Is GPT-5.3 Chat better than Mixtral 8x22B?
GPT-5.3 Chat is the stronger model overall, scoring 42.8 to 27.1 on the Noometry Index. Mixtral 8x22B costs 1.6× less per token, which makes it the better buy when GPT-5.3 Chat's lead doesn't matter for your workload.
Which is cheaper, GPT-5.3 Chat or Mixtral 8x22B?
Mixtral 8x22B is cheaper. It lists at $2 per million input tokens and $6 per million output tokens; GPT-5.3 Chat lists at $1.75 and $14.
Is GPT-5.3 Chat or Mixtral 8x22B better for coding?
GPT-5.3 Chat scores higher on coding benchmarks: 41.4 versus 24.2 in the Noometry coding category.
Which has the bigger context window?
GPT-5.3 Chat does, with 128K tokens against 64K.
How many benchmarks do GPT-5.3 Chat and Mixtral 8x22B share?
17 benchmarks have published results for both models. GPT-5.3 Chat has 18 scored results on Noometry and Mixtral 8x22B has 34.