Mistral Small 4 vs Qwen3.6 35B A3B
Qwen3.6 35B A3B leads Mistral Small 4 on the Artificial Analysis Intelligence Index, 18.2 to 11.3, and Mistral Small 4 costs 1.7x less per output token ($0.60 vs $1.00 per million). Updated October 22, 2026; 12 benchmarks have a result for both.
Mistral Small 4 or Qwen3.6 35B A3B: which to pick
Neither model has a coding score yet, so the two cannot be ranked on coding.
Pick Mistral Small 4 for output tokens 1.7x cheaper ($0.60 vs $1.00 per million) and work measured by AA Coding Index or Terminal-Bench Hard (Artificial Analysis run), where it leads.
- Shared results
- 12
- Mistral Small 4 only
- 3
- Qwen3.6 35B A3B only
- 8
- Like-for-like categories
- 5 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
Qwen3.6 35B A3B
Qwen3.6 35B A3B leads, 18.2 against 11.3.
Same board, both measured
Agentic work
AA Agentic Index
Qwen3.6 35B A3B
Qwen3.6 35B A3B leads, 13.1 against 0.8.
Same board, both measured
Long documents
Listed context window
No call
Both take 262K tokens.
Listed by OpenRouter
Everyday cost
1K input + 500 output tokens
Mistral Small 4
Mistral Small 4 $0.0004, Qwen3.6 35B A3B $0.0006 per turn.
List prices
At a glance
- Coding index
- Mistral Small 4 not benchmarked, Qwen3.6 35B A3B not benchmarked.
- Widest category
- Agentic work, 33.2 points apart on average over 2 shared benchmarks.
- Widest single gap
- τ²-Bench Telecom: Mistral Small 4 41.2% against Qwen3.6 35B A3B 95.3%, 54.1 points apart on a 0 to 100 scale.
- Output price
- Mistral Small 4 $0.60 against Qwen3.6 35B A3B $1.00 per million output tokens, 1.7x apart.
- Context window
- Both take 262K tokens.
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 | Mistral Small 4 | Bars | Qwen3.6 35B A3B | Ties |
|---|---|---|---|---|
| Coding | 1 | 2 | ||
| Intelligence | 0 | 1 | ||
| Agentic work | 0 | 2 | ||
| Reasoning | 0 | 2 | ||
| General | 0 | 4 | ||
| All shared boards | 1 | 11 |
CodingLike-for-likeSix of these boards feed the Vibe Coding Index12
| Benchmark | Mistral Small 4 | Qwen3.6 35B A3B | Leader |
|---|---|---|---|
| AA Coding Index | 26.6 | 41.9 | Qwen3.6 35B A3B |
| Vibe Code Bench (Vals AI) | 0.0% | Not measured | Only Mistral Small 4 measured |
| SciCode | 38.8% | 36.6% | Mistral Small 4 |
| Terminal-Bench Hard (Artificial Analysis run) | 17.4% | 34.8% | Qwen3.6 35B A3B |
| Terminal-Bench | Not measured | 24.6% | Only Qwen3.6 35B A3B measured |
| WeirdML | Not measured | 34.5% | Only Qwen3.6 35B A3B measured |
| ALE-Bench | 497.6 | Not measured | Only Mistral Small 4 measured |
| Neither model has a result on the other 32 boards here | |||
IntelligenceLike-for-likePublic boards, shown as published, kept out of the index01
| Benchmark | Mistral Small 4 | Qwen3.6 35B A3B | Leader |
|---|---|---|---|
| AA Intelligence Index | 11.3 | 18.2 | Qwen3.6 35B A3B |
| Epoch Capabilities Index | Not measured | 143.7 | Only Qwen3.6 35B A3B measured |
Agentic workLike-for-likePublic boards, shown as published, kept out of the index02
| Benchmark | Mistral Small 4 | Qwen3.6 35B A3B | Leader |
|---|---|---|---|
| AA Agentic Index | 0.8 | 13.1 | Qwen3.6 35B A3B |
| τ²-Bench Telecom | 41.2% | 95.3% | Qwen3.6 35B A3B |
| Neither model has a result on the other 39 boards here | |||
ReasoningLike-for-likePublic boards, shown as published, kept out of the index02
| Benchmark | Mistral Small 4 | Qwen3.6 35B A3B | Leader |
|---|---|---|---|
| GPQA Diamond (Artificial Analysis run) | 76.9% | 84.1% | Qwen3.6 35B A3B |
| Humanity's Last Exam (Artificial Analysis run) | 9.9% | 22.2% | Qwen3.6 35B A3B |
| GPQA Diamond (Epoch AI run) | Not measured | 84.8% | Only Qwen3.6 35B A3B measured |
| Mystery game puzzles | Not measured | 22.0% | Only Qwen3.6 35B A3B measured |
| Kagi LLM Benchmark | 40.5% | Not measured | Only Mistral Small 4 measured |
| Neither model has a result on the other 17 boards here | |||
MathDirectional onlyPublic boards, shown as published, kept out of the index2 boards, none shared
| Benchmark | Mistral Small 4 | Qwen3.6 35B A3B | Leader |
|---|---|---|---|
| OTIS Mock AIME | Not measured | 86.7% | Only Qwen3.6 35B A3B measured |
| FrontierMath, tiers 1 to 3 | Not measured | 20.4% | Only Qwen3.6 35B A3B 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 | Mistral Small 4 | Qwen3.6 35B A3B | 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 | Mistral Small 4 | Qwen3.6 35B A3B | Leader |
|---|---|---|---|
| Neither model has a result on 9 boards here | |||
GeneralLike-for-likePublic boards, shown as published, kept out of the index04
| Benchmark | Mistral Small 4 | Qwen3.6 35B A3B | Leader |
|---|---|---|---|
| IFBench | 48.2% | 64.4% | Qwen3.6 35B A3B |
| Long context reasoning (AA-LCR) | 49.7% | 71.7% | Qwen3.6 35B A3B |
| DTBench | 70.9% | 73.9% | Qwen3.6 35B A3B |
| LMCA | 20.6% | 29.7% | Qwen3.6 35B A3B |
| Surface Evolver Bench | Not measured | 44.4% | Only Qwen3.6 35B A3B measured |
| Neither model has a result on the other 41 boards here | |||
Image generationNot comparablePublic boards, shown as published, kept out of the index0 boards, none shared
| Benchmark | Mistral Small 4 | Qwen3.6 35B A3B | 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
Qwen3.6 35B A3B costs less
Agent loop
200K input + 10K output tokens
Qwen3.6 35B A3B 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 | Mistral Small 4 | Qwen3.6 35B A3B |
|---|---|---|
| Maker | Mistral AI | Qwen |
| Weights | Open weights | Open weights |
| Released | March 16, 2026 | April 27, 2026 |
| Context window | 262K | 262K |
| Input $/Mtok | $0.15 | $0.10 |
| Output $/Mtok | $0.60 | $1.00 |
| Coding index | Not benchmarked | Not benchmarked |
| Independent measurements behind it | 1 | 0 |
| Cost per solved task | Not computable | Not computable |
| Source | OpenRouter listing | OpenRouter listing |
Questions
Is Mistral Small 4 better than Qwen3.6 35B A3B for coding?
Neither model has a coding score yet, so the two cannot be ranked on coding. Pick Mistral Small 4 for output tokens 1.7x cheaper ($0.60 vs $1.00 per million) and work measured by AA Coding Index or Terminal-Bench Hard (Artificial Analysis run), where it leads.
Which is cheaper, Mistral Small 4 or Qwen3.6 35B A3B?
Mistral Small 4 costs $0.15 per million input tokens and $0.60 per million output tokens; Qwen3.6 35B A3B costs $0.10 and $1.00. Cost per solved task is known for neither of them.
Which has the bigger context window, Mistral Small 4 or Qwen3.6 35B A3B?
Neither: both take 262K tokens.
How many benchmarks is the Mistral Small 4 vs Qwen3.6 35B A3B comparison based on?
12 benchmarks have a result for both models as of October 22, 2026. Mistral Small 4's coding index rests on 1 independent benchmark and Qwen3.6 35B A3B's on 0. Where only one model has a result, the page says so instead of naming a winner.