Mistral Nemo vs Qwen3.6 35B A3B
Mistral Nemo costs 6.7x less per output token than Qwen3.6 35B A3B ($0.15 vs $1.00 per million). Updated October 22, 2026; 2 benchmarks have a result for both.
Mistral Nemo 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 Nemo for output tokens 6.7x cheaper ($0.15 vs $1.00 per million) and work measured by Epoch Capabilities Index or DTBench, where it leads.
- Shared results
- 2
- Mistral Nemo only
- 1
- Qwen3.6 35B A3B only
- 18
- Like-for-like categories
- 2 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 Qwen3.6 35B A3B has a AA Intelligence Index result, 18.2.
Directional only
Agentic work
AA Agentic Index
No call
Only Qwen3.6 35B A3B has a AA Agentic Index result, 13.1.
Directional only
Long documents
Listed context window
Qwen3.6 35B A3B
Qwen3.6 35B A3B takes 262K tokens against 131K.
Listed by OpenRouter
Everyday cost
1K input + 500 output tokens
Mistral Nemo
Mistral Nemo $0.0002, Qwen3.6 35B A3B $0.0006 per turn.
List prices
At a glance
- Coding index
- Mistral Nemo not benchmarked, Qwen3.6 35B A3B not benchmarked.
- Widest category
- Intelligence, 31.3 points apart on average over 1 shared benchmark.
- Widest single gap
- Epoch Capabilities Index: Mistral Nemo 118.7 against Qwen3.6 35B A3B 143.7, 31.3 points apart on a 0 to 100 scale.
- Output price
- Mistral Nemo $0.15 against Qwen3.6 35B A3B $1.00 per million output tokens, 6.7x apart.
- Context window
- Mistral Nemo takes 131K tokens, Qwen3.6 35B A3B 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 | Mistral Nemo | Bars | Qwen3.6 35B A3B | Ties |
|---|---|---|---|---|
| Intelligence | 0 | 1 | ||
| General | 0 | 1 | ||
| All shared boards | 0 | 2 |
CodingDirectional onlySix of these boards feed the Vibe Coding Index5 boards, none shared
| Benchmark | Mistral Nemo | Qwen3.6 35B A3B | Leader |
|---|---|---|---|
| AA Coding Index | Not measured | 41.9 | Only Qwen3.6 35B A3B measured |
| SciCode | Not measured | 36.6% | Only Qwen3.6 35B A3B measured |
| Terminal-Bench Hard (Artificial Analysis run) | Not measured | 34.8% | Only Qwen3.6 35B A3B measured |
| Terminal-Bench | Not measured | 24.6% | Only Qwen3.6 35B A3B measured |
| WeirdML | Not measured | 34.5% | Only Qwen3.6 35B A3B measured |
| Neither model has a result on the other 34 boards here | |||
IntelligenceLike-for-likePublic boards, shown as published, kept out of the index01
| Benchmark | Mistral Nemo | Qwen3.6 35B A3B | Leader |
|---|---|---|---|
| AA Intelligence Index | Not measured | 18.2 | Only Qwen3.6 35B A3B measured |
| Epoch Capabilities Index | 118.7 | 143.7 | Qwen3.6 35B A3B |
Agentic workDirectional onlyPublic boards, shown as published, kept out of the index2 boards, none shared
| Benchmark | Mistral Nemo | Qwen3.6 35B A3B | Leader |
|---|---|---|---|
| AA Agentic Index | Not measured | 13.1 | Only Qwen3.6 35B A3B measured |
| τ²-Bench Telecom | Not measured | 95.3% | Only Qwen3.6 35B A3B measured |
| Neither model has a result on the other 39 boards here | |||
ReasoningDirectional onlyPublic boards, shown as published, kept out of the index4 boards, none shared
| Benchmark | Mistral Nemo | Qwen3.6 35B A3B | Leader |
|---|---|---|---|
| GPQA Diamond (Artificial Analysis run) | Not measured | 84.1% | Only Qwen3.6 35B A3B measured |
| Humanity's Last Exam (Artificial Analysis run) | Not measured | 22.2% | Only Qwen3.6 35B A3B measured |
| 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 |
| Neither model has a result on the other 18 boards here | |||
MathDirectional onlyPublic boards, shown as published, kept out of the index2 boards, none shared
| Benchmark | Mistral Nemo | 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 | |||
KnowledgeDirectional onlyPublic boards, shown as published, kept out of the index1 board, none shared
| Benchmark | Mistral Nemo | Qwen3.6 35B A3B | Leader |
|---|---|---|---|
| MMLU | 65.3% | Not measured | Only Mistral Nemo measured |
| Neither model has a result on the other 17 boards here | |||
Web designNot comparablePublic boards, shown as published, kept out of the index0 boards, none shared
| Benchmark | Mistral Nemo | 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 index01
| Benchmark | Mistral Nemo | Qwen3.6 35B A3B | Leader |
|---|---|---|---|
| IFBench | Not measured | 64.4% | Only Qwen3.6 35B A3B measured |
| Long context reasoning (AA-LCR) | Not measured | 71.7% | Only Qwen3.6 35B A3B measured |
| DTBench | 48.6% | 73.9% | Qwen3.6 35B A3B |
| LMCA | Not measured | 29.7% | Only Qwen3.6 35B A3B measured |
| 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 Nemo | 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 Nemo costs less
Repository review
50K input + 3K output tokens
Mistral Nemo 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 Nemo | Qwen3.6 35B A3B |
|---|---|---|
| Maker | Mistral AI | Qwen |
| Weights | Open weights | Open weights |
| Released | July 19, 2024 | April 27, 2026 |
| Context window | 131K | 262K |
| Input $/Mtok | $0.15 | $0.10 |
| Output $/Mtok | $0.15 | $1.00 |
| 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 Mistral Nemo 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 Nemo for output tokens 6.7x cheaper ($0.15 vs $1.00 per million) and work measured by Epoch Capabilities Index or DTBench, where it leads.
Which is cheaper, Mistral Nemo or Qwen3.6 35B A3B?
Mistral Nemo costs $0.15 per million input tokens and $0.15 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 Nemo or Qwen3.6 35B A3B?
Qwen3.6 35B A3B, with 262K tokens against 131K.
How many benchmarks is the Mistral Nemo vs Qwen3.6 35B A3B comparison based on?
2 benchmarks have a result for both models as of October 22, 2026. Mistral Nemo's coding index rests on 0 independent benchmarks and Qwen3.6 35B A3B's on 0. Where only one model has a result, the page says so instead of naming a winner.