GPT-4o vs Mistral Small 3.1 24B
Mistral Small 3.1 24B costs 18.0x less per output token than GPT-4o ($0.555 vs $10.00 per million). Updated October 22, 2026; no benchmark has tested both models yet.
- Coding
- No data
- Overall
- No data
- Output $/M
- $10.00
- Coding
- No data
- Overall
- No data
- Output $/M
- $0.555
GPT-4o or Mistral Small 3.1 24B: which to pick
Neither model has a coding score yet, so the two cannot be ranked on coding.
Compare them on price, context and the boards below.
No benchmark has tested both yet. GPT-4o has results on SWE-bench Verified, SWE-bench Lite and SWE-bench (full test set); Mistral Small 3.1 24B on LMArena Text: coding, LMArena Text: software and IT and LMArena Text: hard prompts. Compare them on price and context instead.
Which one for your work
Each card is decided by one number both models carry. Where only one has it, the card says so and makes no call.
Coding
Vibe Coding Index, six public coding benchmarks
No call
Neither has a coding score yet.
One side not measured
Web design
Design Arena: websites
No call
Only GPT-4o has a Design Arena: websites result, 831.
Directional only
Long documents
Listed context window
No call
Both take 128K tokens.
Listed by OpenRouter
Everyday cost
1K input + 500 output tokens
Mistral Small 3.1 24B
GPT-4o $0.0075, Mistral Small 3.1 24B $0.0006 per turn.
List prices
At a glance
- Coding index
- GPT-4o not benchmarked, Mistral Small 3.1 24B not benchmarked.
- Widest category
- None yet: no category has been tested on both models.
- Widest single gap
- None yet: no benchmark has tested both models.
- Output price
- GPT-4o $10.00 against Mistral Small 3.1 24B $0.555 per million output tokens, 18.0x apart.
- Context window
- Both take 128K tokens.
Benchmark by benchmark
Every board either model has a result on, a category to a fold; bars are each result on a 0 to 100 scale. Only one model is measured on each, so no row names a leader.
CodingDirectional onlySix of these boards feed the Vibe Coding Index9 boards measured
| Benchmark | GPT-4o | Mistral Small 3.1 24B | Leader |
|---|---|---|---|
| SWE-bench Verified | 38.8% | Not measured | Only GPT-4o measured |
| SWE-bench Lite | 38.0% | Not measured | Only GPT-4o measured |
| SWE-bench (full test set) | 18.8% | Not measured | Only GPT-4o measured |
| SWE-bench Multimodal | 30.4% | Not measured | Only GPT-4o measured |
| LiveCodeBench (Artificial Analysis run) | 30.9% | Not measured | Only GPT-4o measured |
| Terminal-Bench Hard (Artificial Analysis run) | 8.3% | Not measured | Only GPT-4o measured |
| LMArena Text: coding | Not measured | 1309 | Only Mistral Small 3.1 24B measured |
| LMArena Text: software and IT | Not measured | 1301 | Only Mistral Small 3.1 24B measured |
| SciCode | 1.5% | Not measured | Only GPT-4o measured |
| Neither model has a result on the other 30 boards here | |||
Agentic workDirectional onlyPublic boards, shown as published, kept out of the index2 boards measured
| Benchmark | GPT-4o | Mistral Small 3.1 24B | Leader |
|---|---|---|---|
| τ²-Bench Telecom | 25.1% | Not measured | Only GPT-4o measured |
| GDPval | 9.9% | Not measured | Only GPT-4o measured |
| Neither model has a result on the other 39 boards here | |||
ReasoningDirectional onlyPublic boards, shown as published, kept out of the index9 boards measured
| Benchmark | GPT-4o | Mistral Small 3.1 24B | Leader |
|---|---|---|---|
| GPQA Diamond (Artificial Analysis run) | 54.3% | Not measured | Only GPT-4o measured |
| Humanity's Last Exam (Artificial Analysis run) | 2.4% | Not measured | Only GPT-4o measured |
| ARC-AGI | 4.5% | Not measured | Only GPT-4o measured |
| ARC-AGI-2 | 0.0% | Not measured | Only GPT-4o measured |
| LMArena Text: hard prompts | Not measured | 1278 | Only Mistral Small 3.1 24B measured |
| LMArena Text: expert | Not measured | 1257 | Only Mistral Small 3.1 24B measured |
| LMArena Text: hard prompts in English | Not measured | 1290 | Only Mistral Small 3.1 24B measured |
| LMArena Vision: diagrams | Not measured | 1119 | Only Mistral Small 3.1 24B measured |
| LMArena Vision: homework | Not measured | 1158 | Only Mistral Small 3.1 24B measured |
| Neither model has a result on the other 13 boards here | |||
MathDirectional onlyPublic boards, shown as published, kept out of the index4 boards measured
| Benchmark | GPT-4o | Mistral Small 3.1 24B | Leader |
|---|---|---|---|
| AA Math Index | 6.0 | Not measured | Only GPT-4o measured |
| AIME 2025 (Artificial Analysis run) | 6.0% | Not measured | Only GPT-4o measured |
| LMArena Text: math | Not measured | 1261 | Only Mistral Small 3.1 24B measured |
| LMArena Text: mathematical work | Not measured | 1271 | Only Mistral Small 3.1 24B measured |
| Neither model has a result on the other 9 boards here | |||
KnowledgeDirectional onlyPublic boards, shown as published, kept out of the index6 boards measured
| Benchmark | GPT-4o | Mistral Small 3.1 24B | Leader |
|---|---|---|---|
| MMLU Pro (Artificial Analysis run) | 74.8% | Not measured | Only GPT-4o measured |
| MMLU | 88.1% | Not measured | Only GPT-4o measured |
| LMArena Text: science | Not measured | 1265 | Only Mistral Small 3.1 24B measured |
| LMArena Text: medicine and healthcare | Not measured | 1267 | Only Mistral Small 3.1 24B measured |
| LMArena Text: legal and government | Not measured | 1271 | Only Mistral Small 3.1 24B measured |
| LMArena Text: business and finance | Not measured | 1257 | Only Mistral Small 3.1 24B measured |
| Neither model has a result on the other 12 boards here | |||
Web designDirectional onlyPublic boards, shown as published, kept out of the index6 boards measured
| Benchmark | GPT-4o | Mistral Small 3.1 24B | Leader |
|---|---|---|---|
| Design Arena: websites | 831 | Not measured | Only GPT-4o measured |
| Design Arena: UI components | 882 | Not measured | Only GPT-4o measured |
| Design Arena: game dev | 906 | Not measured | Only GPT-4o measured |
| Design Arena: data viz | 858 | Not measured | Only GPT-4o measured |
| Design Arena: 3D | 868 | Not measured | Only GPT-4o measured |
| Design Arena: all code categories | 860 | Not measured | Only GPT-4o measured |
| Neither model has a result on the other 3 boards here | |||
GeneralDirectional onlyPublic boards, shown as published, kept out of the index29 boards measured
| Benchmark | GPT-4o | Mistral Small 3.1 24B | Leader |
|---|---|---|---|
| IFBench | 34.3% | Not measured | Only GPT-4o measured |
| Long context reasoning (AA-LCR) | 49.3% | Not measured | Only GPT-4o measured |
| DTBench | 64.5% | Not measured | Only GPT-4o measured |
| LMCA | 16.6% | Not measured | Only GPT-4o measured |
| LMArena Text | Not measured | 1277 | Only Mistral Small 3.1 24B measured |
| LMArena Text: instruction following | Not measured | 1263 | Only Mistral Small 3.1 24B measured |
| LMArena Text: creative writing | Not measured | 1252 | Only Mistral Small 3.1 24B measured |
| LMArena Vision | Not measured | 1136 | Only Mistral Small 3.1 24B measured |
| LMArena Text: English | Not measured | 1295 | Only Mistral Small 3.1 24B measured |
| LMArena Text: non-English | Not measured | 1255 | Only Mistral Small 3.1 24B measured |
| LMArena Text: Chinese | Not measured | 1253 | Only Mistral Small 3.1 24B measured |
| LMArena Text: German | Not measured | 1266 | Only Mistral Small 3.1 24B measured |
| LMArena Text: Japanese | Not measured | 1208 | Only Mistral Small 3.1 24B measured |
| LMArena Text: Korean | Not measured | 1207 | Only Mistral Small 3.1 24B measured |
| LMArena Text: French | Not measured | 1273 | Only Mistral Small 3.1 24B measured |
| LMArena Text: Spanish | Not measured | 1284 | Only Mistral Small 3.1 24B measured |
| LMArena Text: Russian | Not measured | 1263 | Only Mistral Small 3.1 24B measured |
| LMArena Text: Polish | Not measured | 1242 | Only Mistral Small 3.1 24B measured |
| LMArena Text: multi-turn | Not measured | 1270 | Only Mistral Small 3.1 24B measured |
| LMArena Text: longer queries | Not measured | 1299 | Only Mistral Small 3.1 24B measured |
| LMArena Text: writing and language | Not measured | 1268 | Only Mistral Small 3.1 24B measured |
| LMArena Text: entertainment and media | Not measured | 1250 | Only Mistral Small 3.1 24B measured |
| LMArena Vision: English | Not measured | 1157 | Only Mistral Small 3.1 24B measured |
| LMArena Vision: Chinese | Not measured | 1155 | Only Mistral Small 3.1 24B measured |
| LMArena Vision: reading text | Not measured | 1132 | Only Mistral Small 3.1 24B measured |
| LMArena Vision: humor | Not measured | 1142 | Only Mistral Small 3.1 24B measured |
| LMArena Vision: captioning | Not measured | 1153 | Only Mistral Small 3.1 24B measured |
| LMArena Vision: recognizing things | Not measured | 1155 | Only Mistral Small 3.1 24B measured |
| LMArena Vision: creative writing | Not measured | 1123 | Only Mistral Small 3.1 24B measured |
| Neither model has a result on the other 17 boards here | |||
What each workload costs
Three fixed token mixes at each model's listed price, so per-token rates become a bill.
Chat turn
1K input + 500 output tokens
Mistral Small 3.1 24B costs less
Repository review
50K input + 3K output tokens
Mistral Small 3.1 24B costs less
Agent loop
200K input + 10K output tokens
Mistral Small 3.1 24B costs less
Listed OpenRouter rates, without cache or batch discounts. A workload that does not fit a model's context window would need splitting.
Specification differences
The leading value in a row is marked; a row with a missing value names no leader. Our two rows are marked in red.
| Specification | OpenAI GPT-4o | Mistral Small 3.1 24B |
|---|---|---|
| Maker | OpenAI | Mistral AI |
| Weights | No public weights listed | Open weights |
| Released | May 13, 2024 | March 17, 2025 |
| Context window | 128K | 128K |
| Input $/Mtok | $2.50 | $0.351 |
| Output $/Mtok | $10.00 | $0.555 |
| Coding index | Not benchmarked | Not benchmarked |
| Independent measurements behind it | 0 | 0 |
| Cost per solved task | Not computable | Not computable |
| Source | OpenRouter listing | OpenRouter listing |
Questions
Is GPT-4o better than Mistral Small 3.1 24B for coding?
Neither model has a coding score yet, so the two cannot be ranked on coding. Compare them on price, context and the boards below.
Which is cheaper, GPT-4o or Mistral Small 3.1 24B?
GPT-4o costs $2.50 per million input tokens and $10.00 per million output tokens; Mistral Small 3.1 24B costs $0.351 and $0.555. Cost per solved task is known for neither of them.
Which has the bigger context window, GPT-4o or Mistral Small 3.1 24B?
Neither: both take 128K tokens.
Has any benchmark tested both GPT-4o and Mistral Small 3.1 24B?
No benchmark has tested both yet. GPT-4o has results on SWE-bench Verified, SWE-bench Lite and SWE-bench (full test set); Mistral Small 3.1 24B on LMArena Text: coding, LMArena Text: software and IT and LMArena Text: hard prompts. Compare them on price and context instead. Data as of October 22, 2026.