GPT-5.5 Pro vs Mistral Small 4
Mistral Small 4 costs 300.0x less per output token than GPT-5.5 Pro ($0.60 vs $180.00 per million). Updated October 21, 2026; 2 benchmarks have a result for both.
GPT-5.5 Pro or Mistral Small 4: which to pick
Neither model has a coding score yet, so the two cannot be ranked on coding.
Pick GPT-5.5 Pro for a larger context window (1.05M against 262K tokens).
- Shared results
- 2
- GPT-5.5 Pro only
- 7
- Mistral Small 4 only
- 13
- Like-for-like categories
- 1 of 9
Only benchmarks that tested both models count toward a pick; a result only one model has is shown but not compared.
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
GPT-5.5 Pro
GPT-5.5 Pro takes 1.05M tokens against 262K.
Listed by OpenRouter
Everyday cost
1K input + 500 output tokens
Mistral Small 4
GPT-5.5 Pro $0.120, Mistral Small 4 $0.0004 per turn.
List prices
At a glance
- Coding index
- GPT-5.5 Pro not benchmarked, Mistral Small 4 not benchmarked.
- Widest category
- General, 29.2 points apart on average over 2 shared benchmarks.
- Widest single gap
- LMCA: GPT-5.5 Pro 53.9% against Mistral Small 4 20.6%, 33.3 points apart on a 0 to 100 scale.
- Output price
- GPT-5.5 Pro $180.00 against Mistral Small 4 $0.60 per million output tokens, 300.0x apart.
- Context window
- GPT-5.5 Pro takes 1.05M tokens, Mistral Small 4 262K.
Benchmark by benchmark
First the score: boards each model leads, per category, where both have a result. Then every board, a category to a fold; bars are each result on a 0 to 100 scale, so compare the two in a row, not one row with another.
| Category | GPT-5.5 Pro | Bars | Mistral Small 4 | Ties |
|---|---|---|---|---|
| General | 2 | 0 | ||
| All shared boards | 2 | 0 |
CodingDirectional onlySix of these boards feed the Vibe Coding Index5 boards, none shared
| Benchmark | GPT-5.5 Pro | Mistral Small 4 | Leader |
|---|---|---|---|
| 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 |
| ALE-Bench | Not measured | 497.6 | Only Mistral Small 4 measured |
| Neither model has a result on the other 34 boards here | |||
IntelligenceDirectional onlyPublic boards, shown as published, kept out of the index2 boards, none shared
| Benchmark | GPT-5.5 Pro | Mistral Small 4 | Leader |
|---|---|---|---|
| AA Intelligence Index | Not measured | 11.3 | Only Mistral Small 4 measured |
| Epoch Capabilities Index | 162.9 | Not measured | Only GPT-5.5 Pro measured |
Agentic workDirectional onlyPublic boards, shown as published, kept out of the index2 boards, none shared
| Benchmark | GPT-5.5 Pro | 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 |
| Neither model has a result on the other 39 boards here | |||
ReasoningDirectional onlyPublic boards, shown as published, kept out of the index7 boards, none shared
| Benchmark | GPT-5.5 Pro | 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 |
| ARC-AGI | 96.5% | Not measured | Only GPT-5.5 Pro measured |
| ARC-AGI-2 | 84.6% | Not measured | Only GPT-5.5 Pro measured |
| SimpleBench | 76.9% | Not measured | Only GPT-5.5 Pro measured |
| Chess puzzles | 62.0% | Not measured | Only GPT-5.5 Pro measured |
| Kagi LLM Benchmark | Not measured | 40.5% | Only Mistral Small 4 measured |
| Neither model has a result on the other 15 boards here | |||
MathDirectional onlyPublic boards, shown as published, kept out of the index2 boards, none shared
| Benchmark | GPT-5.5 Pro | Mistral Small 4 | Leader |
|---|---|---|---|
| FrontierMath, tiers 1 to 3 | 87.7% | Not measured | Only GPT-5.5 Pro measured |
| FrontierMath, tier 4 | 78.0% | Not measured | Only GPT-5.5 Pro measured |
| Neither model has a result on the other 11 boards here | |||
KnowledgeNot comparablePublic boards, shown as published, kept out of the index0 boards, none shared
| Benchmark | GPT-5.5 Pro | Mistral Small 4 | Leader |
|---|---|---|---|
| Neither model has a result on 18 boards here | |||
Web designNot comparablePublic boards, shown as published, kept out of the index0 boards, none shared
| Benchmark | GPT-5.5 Pro | Mistral Small 4 | Leader |
|---|---|---|---|
| Neither model has a result on 9 boards here | |||
GeneralLike-for-likePublic boards, shown as published, kept out of the index20
| Benchmark | GPT-5.5 Pro | 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 | 96.0% | 70.9% | GPT-5.5 Pro |
| LMCA | 53.9% | 20.6% | GPT-5.5 Pro |
| Neither model has a result on the other 42 boards here | |||
Image generationNot comparablePublic boards, shown as published, kept out of the index0 boards, none shared
| Benchmark | GPT-5.5 Pro | Mistral Small 4 | Leader |
|---|---|---|---|
| Neither model has a result on 5 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 4 costs less
Repository review
50K input + 3K output tokens
Mistral Small 4 costs less
Agent loop
200K input + 10K output tokens
Mistral Small 4 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-5.5 Pro | Mistral Small 4 |
|---|---|---|
| Maker | OpenAI | Mistral AI |
| Weights | No public weights listed | Open weights |
| Released | April 24, 2026 | March 16, 2026 |
| Context window | 1.05M | 262K |
| Input $/Mtok | $30.00 | $0.15 |
| Output $/Mtok | $180.00 | $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-5.5 Pro better than Mistral Small 4 for coding?
Neither model has a coding score yet, so the two cannot be ranked on coding. Pick GPT-5.5 Pro for a larger context window (1.05M against 262K tokens).
Which is cheaper, GPT-5.5 Pro or Mistral Small 4?
GPT-5.5 Pro costs $30.00 per million input tokens and $180.00 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-5.5 Pro or Mistral Small 4?
GPT-5.5 Pro, with 1.05M tokens against 262K.
How many benchmarks is the GPT-5.5 Pro vs Mistral Small 4 comparison based on?
2 benchmarks have a result for both models as of October 21, 2026. GPT-5.5 Pro's coding index rests on 0 independent benchmarks and Mistral Small 4's on 1. Where only one model has a result, the page says so instead of naming a winner.