GPT-4o-mini (2024-07-18) vs Mistral Small 4
GPT-4o-mini (2024-07-18) and Mistral Small 4 cost about the same per output token ($0.60 vs $0.60 per million). Updated October 22, 2026; no benchmark has tested both models yet.
- Coding
- No data
- Overall
- No data
- Output $/M
- $0.60
- Coding
- No data
- Overall
- No data
- Output $/M
- $0.60
GPT-4o-mini (2024-07-18) or Mistral Small 4: 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-mini (2024-07-18) has results on Aider polyglot, WeirdML and LMArena Text: coding; Mistral Small 4 on AA Coding Index, Vibe Code Bench (Vals AI) and SciCode. 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
Intelligence
AA Intelligence Index
No call
Only Mistral Small 4 has a AA Intelligence Index result, 11.3.
Directional only
Agentic work
AA Agentic Index
No call
Only Mistral Small 4 has a AA Agentic Index result, 0.8.
Directional only
Long documents
Listed context window
Mistral Small 4
Mistral Small 4 takes 262K tokens against 128K.
Listed by OpenRouter
Everyday cost
1K input + 500 output tokens
No call
GPT-4o-mini (2024-07-18) $0.0004, Mistral Small 4 $0.0004 per turn.
List prices
At a glance
- Coding index
- GPT-4o-mini (2024-07-18) not benchmarked, Mistral Small 4 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
- Both cost $0.60 per million output tokens.
- Context window
- GPT-4o-mini (2024-07-18) takes 128K tokens, Mistral Small 4 262K.
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-mini (2024-07-18) | Mistral Small 4 | Leader |
|---|---|---|---|
| Aider polyglot | 3.6% | Not measured | Only GPT-4o-mini (2024-07-18) measured |
| AA Coding Index | Not measured | 26.6 | Only Mistral Small 4 measured |
| Vibe Code Bench (Vals AI) | Not measured | 0.0% | Only Mistral Small 4 measured |
| SciCode | Not measured | 38.8% | Only Mistral Small 4 measured |
| Terminal-Bench Hard (Artificial Analysis run) | Not measured | 17.4% | Only Mistral Small 4 measured |
| WeirdML | 11.8% | Not measured | Only GPT-4o-mini (2024-07-18) measured |
| ALE-Bench | Not measured | 497.6 | Only Mistral Small 4 measured |
| LMArena Text: coding | 1290 | Not measured | Only GPT-4o-mini (2024-07-18) measured |
| LMArena Text: software and IT | 1291 | Not measured | Only GPT-4o-mini (2024-07-18) measured |
| Neither model has a result on the other 34 boards here | |||
IntelligenceDirectional onlyPublic boards, shown as published, kept out of the index1 board measured
| Benchmark | GPT-4o-mini (2024-07-18) | Mistral Small 4 | Leader |
|---|---|---|---|
| AA Intelligence Index | Not measured | 11.3 | Only Mistral Small 4 measured |
| Neither model has a result on the other 1 board here | |||
Agentic workDirectional onlyPublic boards, shown as published, kept out of the index3 boards measured
| Benchmark | GPT-4o-mini (2024-07-18) | Mistral Small 4 | Leader |
|---|---|---|---|
| AA Agentic Index | Not measured | 0.8 | Only Mistral Small 4 measured |
| τ²-Bench Telecom | Not measured | 41.2% | Only Mistral Small 4 measured |
| BALROG | 17.4% | Not measured | Only GPT-4o-mini (2024-07-18) measured |
| Neither model has a result on the other 39 boards here | |||
ReasoningDirectional onlyPublic boards, shown as published, kept out of the index11 boards measured
| Benchmark | GPT-4o-mini (2024-07-18) | Mistral Small 4 | Leader |
|---|---|---|---|
| GPQA Diamond (Artificial Analysis run) | Not measured | 76.9% | Only Mistral Small 4 measured |
| Humanity's Last Exam (Artificial Analysis run) | Not measured | 9.9% | Only Mistral Small 4 measured |
| GPQA Diamond (Epoch AI run) | 37.7% | Not measured | Only GPT-4o-mini (2024-07-18) measured |
| SimpleBench | 10.7% | Not measured | Only GPT-4o-mini (2024-07-18) measured |
| Chess puzzles | 3.0% | Not measured | Only GPT-4o-mini (2024-07-18) measured |
| Mystery game puzzles | 12.0% | Not measured | Only GPT-4o-mini (2024-07-18) measured |
| VPCT | 34.0% | Not measured | Only GPT-4o-mini (2024-07-18) measured |
| LMArena Text: hard prompts | 1267 | Not measured | Only GPT-4o-mini (2024-07-18) measured |
| LMArena Text: expert | 1234 | Not measured | Only GPT-4o-mini (2024-07-18) measured |
| LMArena Text: hard prompts in English | 1278 | Not measured | Only GPT-4o-mini (2024-07-18) measured |
| Kagi LLM Benchmark | Not measured | 40.5% | Only Mistral Small 4 measured |
| Neither model has a result on the other 12 boards here | |||
MathDirectional onlyPublic boards, shown as published, kept out of the index5 boards measured
| Benchmark | GPT-4o-mini (2024-07-18) | Mistral Small 4 | Leader |
|---|---|---|---|
| OTIS Mock AIME | 6.9% | Not measured | Only GPT-4o-mini (2024-07-18) measured |
| FrontierMath, tiers 1 to 3 | 0.7% | Not measured | Only GPT-4o-mini (2024-07-18) measured |
| MATH level 5 | 52.6% | Not measured | Only GPT-4o-mini (2024-07-18) measured |
| LMArena Text: math | 1267 | Not measured | Only GPT-4o-mini (2024-07-18) measured |
| LMArena Text: mathematical work | 1271 | Not measured | Only GPT-4o-mini (2024-07-18) measured |
| Neither model has a result on the other 9 boards here | |||
KnowledgeDirectional onlyPublic boards, shown as published, kept out of the index7 boards measured
| Benchmark | GPT-4o-mini (2024-07-18) | Mistral Small 4 | Leader |
|---|---|---|---|
| SimpleQA Verified | 8.3% | Not measured | Only GPT-4o-mini (2024-07-18) measured |
| MMLU | 76.7% | Not measured | Only GPT-4o-mini (2024-07-18) measured |
| GeoBench | 64.0% | Not measured | Only GPT-4o-mini (2024-07-18) measured |
| LMArena Text: science | 1286 | Not measured | Only GPT-4o-mini (2024-07-18) measured |
| LMArena Text: medicine and healthcare | 1282 | Not measured | Only GPT-4o-mini (2024-07-18) measured |
| LMArena Text: legal and government | 1305 | Not measured | Only GPT-4o-mini (2024-07-18) measured |
| LMArena Text: business and finance | 1265 | Not measured | Only GPT-4o-mini (2024-07-18) measured |
| Neither model has a result on the other 13 boards here | |||
GeneralDirectional onlyPublic boards, shown as published, kept out of the index25 boards measured
| Benchmark | GPT-4o-mini (2024-07-18) | Mistral Small 4 | Leader |
|---|---|---|---|
| IFBench | Not measured | 48.2% | Only Mistral Small 4 measured |
| Long context reasoning (AA-LCR) | Not measured | 49.7% | Only Mistral Small 4 measured |
| DTBench | Not measured | 70.9% | Only Mistral Small 4 measured |
| LMCA | Not measured | 20.6% | Only Mistral Small 4 measured |
| Creative writing (Lech Mazur) | 67.2% | Not measured | Only GPT-4o-mini (2024-07-18) measured |
| LMArena Text | 1286 | Not measured | Only GPT-4o-mini (2024-07-18) measured |
| LMArena Text: instruction following | 1258 | Not measured | Only GPT-4o-mini (2024-07-18) measured |
| LMArena Text: creative writing | 1268 | Not measured | Only GPT-4o-mini (2024-07-18) measured |
| LMArena Vision | 1066 | Not measured | Only GPT-4o-mini (2024-07-18) measured |
| LMArena Text: English | 1301 | Not measured | Only GPT-4o-mini (2024-07-18) measured |
| LMArena Text: non-English | 1266 | Not measured | Only GPT-4o-mini (2024-07-18) measured |
| LMArena Text: Chinese | 1265 | Not measured | Only GPT-4o-mini (2024-07-18) measured |
| LMArena Text: German | 1272 | Not measured | Only GPT-4o-mini (2024-07-18) measured |
| LMArena Text: Japanese | 1216 | Not measured | Only GPT-4o-mini (2024-07-18) measured |
| LMArena Text: Korean | 1195 | Not measured | Only GPT-4o-mini (2024-07-18) measured |
| LMArena Text: French | 1297 | Not measured | Only GPT-4o-mini (2024-07-18) measured |
| LMArena Text: Spanish | 1276 | Not measured | Only GPT-4o-mini (2024-07-18) measured |
| LMArena Text: Russian | 1275 | Not measured | Only GPT-4o-mini (2024-07-18) measured |
| LMArena Text: Polish | 1244 | Not measured | Only GPT-4o-mini (2024-07-18) measured |
| LMArena Text: multi-turn | 1285 | Not measured | Only GPT-4o-mini (2024-07-18) measured |
| LMArena Text: longer queries | 1289 | Not measured | Only GPT-4o-mini (2024-07-18) measured |
| LMArena Text: writing and language | 1282 | Not measured | Only GPT-4o-mini (2024-07-18) measured |
| LMArena Text: entertainment and media | 1253 | Not measured | Only GPT-4o-mini (2024-07-18) measured |
| LMArena Vision: English | 1072 | Not measured | Only GPT-4o-mini (2024-07-18) measured |
| LMArena Vision: Chinese | 1033 | Not measured | Only GPT-4o-mini (2024-07-18) measured |
| Neither model has a result on the other 23 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
Same cost
Repository review
50K input + 3K output tokens
Same cost
Agent loop
200K input + 10K output tokens
Same cost
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-mini (2024-07-18) | Mistral Small 4 |
|---|---|---|
| Maker | OpenAI | Mistral AI |
| Weights | No public weights listed | Open weights |
| Released | July 18, 2024 | March 16, 2026 |
| Context window | 128K | 262K |
| Input $/Mtok | $0.15 | $0.15 |
| Output $/Mtok | $0.60 | $0.60 |
| Coding index | Not benchmarked | Not benchmarked |
| Independent measurements behind it | 0 | 1 |
| Cost per solved task | Not computable | Not computable |
| Source | OpenRouter listing | OpenRouter listing |
Questions
Is GPT-4o-mini (2024-07-18) better than Mistral Small 4 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-mini (2024-07-18) or Mistral Small 4?
GPT-4o-mini (2024-07-18) costs $0.15 per million input tokens and $0.60 per million output tokens; Mistral Small 4 costs $0.15 and $0.60. Cost per solved task is known for neither of them.
Which has the bigger context window, GPT-4o-mini (2024-07-18) or Mistral Small 4?
Mistral Small 4, with 262K tokens against 128K.
Has any benchmark tested both GPT-4o-mini (2024-07-18) and Mistral Small 4?
No benchmark has tested both yet. GPT-4o-mini (2024-07-18) has results on Aider polyglot, WeirdML and LMArena Text: coding; Mistral Small 4 on AA Coding Index, Vibe Code Bench (Vals AI) and SciCode. Compare them on price and context instead. Data as of October 22, 2026.