Mistral Nemo vs Mixtral 8x22B Instruct
Mistral Nemo costs 40.0x less per output token than Mixtral 8x22B Instruct ($0.15 vs $6.00 per million). Updated October 21, 2026; 2 benchmarks have a result for both.
Mistral Nemo or Mixtral 8x22B Instruct: which to pick
Neither model has a coding score yet, so the two cannot be ranked on coding.
Pick Mistral Nemo for output tokens 40.0x cheaper ($0.15 vs $6.00 per million) and a larger context window (131K against 66K tokens).
- Shared results
- 2
- Mistral Nemo only
- 1
- Mixtral 8x22B Instruct only
- 6
- 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 Mixtral 8x22B Instruct has a AA Intelligence Index result, 5.7.
Directional only
Long documents
Listed context window
Mistral Nemo
Mistral Nemo takes 131K tokens against 66K.
Listed by OpenRouter
Everyday cost
1K input + 500 output tokens
Mistral Nemo
Mistral Nemo $0.0002, Mixtral 8x22B Instruct $0.0050 per turn.
List prices
At a glance
- Coding index
- Mistral Nemo not benchmarked, Mixtral 8x22B Instruct not benchmarked.
- Widest category
- General, 6.5 points apart on average over 1 shared benchmark.
- Widest single gap
- DTBench: Mistral Nemo 48.6% against Mixtral 8x22B Instruct 55.1%, 6.5 points apart on a 0 to 100 scale.
- Output price
- Mistral Nemo $0.15 against Mixtral 8x22B Instruct $6.00 per million output tokens, 40.0x apart.
- Context window
- Mistral Nemo takes 131K tokens, Mixtral 8x22B Instruct 66K.
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 | Mixtral 8x22B Instruct | Ties |
|---|---|---|---|---|
| Intelligence | 0 | 1 | ||
| General | 0 | 1 | ||
| All shared boards | 0 | 2 |
CodingDirectional onlySix of these boards feed the Vibe Coding Index2 boards, none shared
| Benchmark | Mistral Nemo | Mixtral 8x22B Instruct | Leader |
|---|---|---|---|
| LiveCodeBench (Artificial Analysis run) | Not measured | 14.8% | Only Mixtral 8x22B Instruct measured |
| SciCode | Not measured | 0.0% | Only Mixtral 8x22B Instruct measured |
| Neither model has a result on the other 37 boards here | |||
IntelligenceLike-for-likePublic boards, shown as published, kept out of the index01
| Benchmark | Mistral Nemo | Mixtral 8x22B Instruct | Leader |
|---|---|---|---|
| AA Intelligence Index | Not measured | 5.7 | Only Mixtral 8x22B Instruct measured |
| Epoch Capabilities Index | 118.7 | 122.0 | Mixtral 8x22B Instruct |
Agentic workNot comparablePublic boards, shown as published, kept out of the index0 boards, none shared
| Benchmark | Mistral Nemo | Mixtral 8x22B Instruct | Leader |
|---|---|---|---|
| Neither model has a result on 41 boards here | |||
ReasoningDirectional onlyPublic boards, shown as published, kept out of the index2 boards, none shared
| Benchmark | Mistral Nemo | Mixtral 8x22B Instruct | Leader |
|---|---|---|---|
| GPQA Diamond (Artificial Analysis run) | Not measured | 33.2% | Only Mixtral 8x22B Instruct measured |
| Humanity's Last Exam (Artificial Analysis run) | Not measured | 4.0% | Only Mixtral 8x22B Instruct measured |
| Neither model has a result on the other 20 boards here | |||
MathNot comparablePublic boards, shown as published, kept out of the index0 boards, none shared
| Benchmark | Mistral Nemo | Mixtral 8x22B Instruct | Leader |
|---|---|---|---|
| Neither model has a result on 13 boards here | |||
KnowledgeDirectional onlyPublic boards, shown as published, kept out of the index2 boards, none shared
| Benchmark | Mistral Nemo | Mixtral 8x22B Instruct | Leader |
|---|---|---|---|
| MMLU Pro (Artificial Analysis run) | Not measured | 53.7% | Only Mixtral 8x22B Instruct measured |
| MMLU | 65.3% | Not measured | Only Mistral Nemo measured |
| Neither model has a result on the other 16 boards here | |||
Web designNot comparablePublic boards, shown as published, kept out of the index0 boards, none shared
| Benchmark | Mistral Nemo | Mixtral 8x22B Instruct | 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 | Mixtral 8x22B Instruct | Leader |
|---|---|---|---|
| DTBench | 48.6% | 55.1% | Mixtral 8x22B Instruct |
| Neither model has a result on the other 45 boards here | |||
Image generationNot comparablePublic boards, shown as published, kept out of the index0 boards, none shared
| Benchmark | Mistral Nemo | Mixtral 8x22B Instruct | 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
Mistral Nemo 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 | Mistral Mixtral 8x22B Instruct |
|---|---|---|
| Maker | Mistral AI | Mistral AI |
| Weights | Open weights | Open weights |
| Released | July 19, 2024 | April 17, 2024 |
| Context window | 131K | 66K |
| Input $/Mtok | $0.15 | $2.00 |
| Output $/Mtok | $0.15 | $6.00 |
| 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 Mixtral 8x22B Instruct for coding?
Neither model has a coding score yet, so the two cannot be ranked on coding. Pick Mistral Nemo for output tokens 40.0x cheaper ($0.15 vs $6.00 per million) and a larger context window (131K against 66K tokens).
Which is cheaper, Mistral Nemo or Mixtral 8x22B Instruct?
Mistral Nemo costs $0.15 per million input tokens and $0.15 per million output tokens; Mixtral 8x22B Instruct costs $2.00 and $6.00. Cost per solved task is known for neither of them.
Which has the bigger context window, Mistral Nemo or Mixtral 8x22B Instruct?
Mistral Nemo, with 131K tokens against 66K.
How many benchmarks is the Mistral Nemo vs Mixtral 8x22B Instruct comparison based on?
2 benchmarks have a result for both models as of October 21, 2026. Mistral Nemo's coding index rests on 0 independent benchmarks and Mixtral 8x22B Instruct's on 0. Where only one model has a result, the page says so instead of naming a winner.