Gemma 4 31B vs Mixtral 8x22B Instruct
Gemma 4 31B leads Mixtral 8x22B Instruct on the Artificial Analysis Intelligence Index, 14.7 to 5.7, and Gemma 4 31B costs 15.0x less per output token ($0.40 vs $6.00 per million). Updated October 21, 2026; 5 benchmarks have a result for both.
Gemma 4 31B or Mixtral 8x22B Instruct: which to pick
Only Gemma 4 31B has a coding score, 39.0 on the Vibe Coding Index; Mixtral 8x22B Instruct has none, so the two cannot be ranked on coding.
Compare them on price, context and the boards below.
- Shared results
- 5
- Gemma 4 31B only
- 63
- Mixtral 8x22B Instruct only
- 2
- Like-for-like categories
- 3 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
Only Gemma 4 31B has a coding score, so no call is made.
One side not measured
Intelligence
AA Intelligence Index
Gemma 4 31B
Gemma 4 31B leads, 14.7 against 5.7.
Same board, both measured
Agentic work
AA Agentic Index
No call
Only Gemma 4 31B has a AA Agentic Index result, 4.2.
Directional only
Long documents
Listed context window
Gemma 4 31B
Gemma 4 31B takes 262K tokens against 66K.
Listed by OpenRouter
Everyday cost
1K input + 500 output tokens
Gemma 4 31B
Gemma 4 31B $0.0003, Mixtral 8x22B Instruct $0.0050 per turn.
List prices
At a glance
- Coding index
- Gemma 4 31B 39.0 from 2 benchmarks, Mixtral 8x22B Instruct not benchmarked.
- Widest category
- Reasoning, 36.0 points apart on average over 2 shared benchmarks.
- Widest single gap
- GPQA Diamond (Artificial Analysis run): Gemma 4 31B 85.7% against Mixtral 8x22B Instruct 33.2%, 52.5 points apart on a 0 to 100 scale.
- Output price
- Gemma 4 31B $0.40 against Mixtral 8x22B Instruct $6.00 per million output tokens, 15.0x apart.
- Context window
- Gemma 4 31B takes 262K 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 | Gemma 4 31B | Bars | Mixtral 8x22B Instruct | Ties |
|---|---|---|---|---|
| Intelligence | 2 | 0 | ||
| Reasoning | 2 | 0 | ||
| General | 1 | 0 | ||
| All shared boards | 5 | 0 |
CodingDirectional onlySix of these boards feed the Vibe Coding Index12 boards, none shared
| Benchmark | Gemma 4 31B | Mixtral 8x22B Instruct | Leader |
|---|---|---|---|
| LiveBench coding | 49.0% | Not measured | Only Gemma 4 31B measured |
| LMArena WebDev | 1367 | Not measured | Only Gemma 4 31B measured |
| AA Coding Index | 43.4 | Not measured | Only Gemma 4 31B measured |
| LiveCodeBench (Artificial Analysis run) | Not measured | 14.8% | Only Mixtral 8x22B Instruct measured |
| SciCode | 45.5% | Not measured | Only Gemma 4 31B measured |
| Terminal-Bench Hard (Artificial Analysis run) | 36.4% | Not measured | Only Gemma 4 31B measured |
| WeirdML | 52.3% | Not measured | Only Gemma 4 31B measured |
| ALE-Bench | 925.5 | Not measured | Only Gemma 4 31B measured |
| LMArena Text: coding | 1459 | Not measured | Only Gemma 4 31B measured |
| LMArena Text: software and IT | 1463 | Not measured | Only Gemma 4 31B measured |
| LMArena WebDev: React | 1359 | Not measured | Only Gemma 4 31B measured |
| LMArena WebDev: HTML | 1380 | Not measured | Only Gemma 4 31B measured |
| Neither model has a result on the other 26 boards here | |||
IntelligenceLike-for-likePublic boards, shown as published, kept out of the index20
| Benchmark | Gemma 4 31B | Mixtral 8x22B Instruct | Leader |
|---|---|---|---|
| AA Intelligence Index | 14.7 | 5.7 | Gemma 4 31B |
| Epoch Capabilities Index | 143.0 | 122.0 | Gemma 4 31B |
Agentic workDirectional onlyPublic boards, shown as published, kept out of the index5 boards, none shared
| Benchmark | Gemma 4 31B | Mixtral 8x22B Instruct | Leader |
|---|---|---|---|
| AA Agentic Index | 4.2 | Not measured | Only Gemma 4 31B measured |
| LiveBench research | 44.4% | Not measured | Only Gemma 4 31B measured |
| LiveBench browser | 4.0% | Not measured | Only Gemma 4 31B measured |
| LiveBench long agentic | 13.3% | Not measured | Only Gemma 4 31B measured |
| τ²-Bench Telecom | 65.5% | Not measured | Only Gemma 4 31B measured |
| Neither model has a result on the other 34 boards here | |||
ReasoningLike-for-likePublic boards, shown as published, kept out of the index20
| Benchmark | Gemma 4 31B | Mixtral 8x22B Instruct | Leader |
|---|---|---|---|
| LiveBench reasoning | 68.3% | Not measured | Only Gemma 4 31B measured |
| GPQA Diamond (Artificial Analysis run) | 85.7% | 33.2% | Gemma 4 31B |
| Humanity's Last Exam (Artificial Analysis run) | 23.6% | 4.0% | Gemma 4 31B |
| GPQA Diamond (Epoch AI run) | 75.8% | Not measured | Only Gemma 4 31B measured |
| LMArena Text: hard prompts | 1448 | Not measured | Only Gemma 4 31B measured |
| LMArena Text: expert | 1464 | Not measured | Only Gemma 4 31B measured |
| LMArena Text: hard prompts in English | 1456 | Not measured | Only Gemma 4 31B measured |
| LMArena Vision: diagrams | 1283 | Not measured | Only Gemma 4 31B measured |
| LMArena Vision: homework | 1310 | Not measured | Only Gemma 4 31B measured |
| Neither model has a result on the other 12 boards here | |||
MathDirectional onlyPublic boards, shown as published, kept out of the index3 boards, none shared
| Benchmark | Gemma 4 31B | Mixtral 8x22B Instruct | Leader |
|---|---|---|---|
| OTIS Mock AIME | 73.3% | Not measured | Only Gemma 4 31B measured |
| LMArena Text: math | 1463 | Not measured | Only Gemma 4 31B measured |
| LMArena Text: mathematical work | 1465 | Not measured | Only Gemma 4 31B measured |
| Neither model has a result on the other 10 boards here | |||
KnowledgeDirectional onlyPublic boards, shown as published, kept out of the index8 boards, none shared
| Benchmark | Gemma 4 31B | Mixtral 8x22B Instruct | Leader |
|---|---|---|---|
| CaseLaw (Vals AI) | 52.6% | Not measured | Only Gemma 4 31B measured |
| MortgageTax (Vals AI) | 61.4% | Not measured | Only Gemma 4 31B measured |
| MMLU Pro (Artificial Analysis run) | Not measured | 53.7% | Only Mixtral 8x22B Instruct measured |
| SimpleQA Verified | 10.4% | Not measured | Only Gemma 4 31B measured |
| LMArena Text: science | 1457 | Not measured | Only Gemma 4 31B measured |
| LMArena Text: medicine and healthcare | 1451 | Not measured | Only Gemma 4 31B measured |
| LMArena Text: legal and government | 1438 | Not measured | Only Gemma 4 31B measured |
| LMArena Text: business and finance | 1430 | Not measured | Only Gemma 4 31B measured |
| Neither model has a result on the other 9 boards here | |||
Web designDirectional onlyPublic boards, shown as published, kept out of the index1 board, none shared
| Benchmark | Gemma 4 31B | Mixtral 8x22B Instruct | Leader |
|---|---|---|---|
| LiveBench design | 58.4% | Not measured | Only Gemma 4 31B measured |
| Neither model has a result on the other 8 boards here | |||
GeneralLike-for-likePublic boards, shown as published, kept out of the index10
| Benchmark | Gemma 4 31B | Mixtral 8x22B Instruct | Leader |
|---|---|---|---|
| LiveBench data analysis | 53.3% | Not measured | Only Gemma 4 31B measured |
| SAGE (Vals AI) | 55.0% | Not measured | Only Gemma 4 31B measured |
| IFBench | 75.6% | Not measured | Only Gemma 4 31B measured |
| Long context reasoning (AA-LCR) | 69.7% | Not measured | Only Gemma 4 31B measured |
| DTBench | 82.7% | 55.1% | Gemma 4 31B |
| LMCA | 39.3% | Not measured | Only Gemma 4 31B measured |
| Surface Evolver Bench | 30.6% | Not measured | Only Gemma 4 31B measured |
| LMArena Text | 1443 | Not measured | Only Gemma 4 31B measured |
| LMArena Text: instruction following | 1433 | Not measured | Only Gemma 4 31B measured |
| LMArena Text: creative writing | 1417 | Not measured | Only Gemma 4 31B measured |
| LMArena Vision | 1276 | Not measured | Only Gemma 4 31B measured |
| LMArena Text: English | 1451 | Not measured | Only Gemma 4 31B measured |
| LMArena Text: non-English | 1430 | Not measured | Only Gemma 4 31B measured |
| LMArena Text: Chinese | 1475 | Not measured | Only Gemma 4 31B measured |
| LMArena Text: French | 1436 | Not measured | Only Gemma 4 31B measured |
| LMArena Text: Spanish | 1442 | Not measured | Only Gemma 4 31B measured |
| LMArena Text: Russian | 1460 | Not measured | Only Gemma 4 31B measured |
| LMArena Text: Polish | 1433 | Not measured | Only Gemma 4 31B measured |
| LMArena Text: multi-turn | 1452 | Not measured | Only Gemma 4 31B measured |
| LMArena Text: longer queries | 1446 | Not measured | Only Gemma 4 31B measured |
| LMArena Text: writing and language | 1432 | Not measured | Only Gemma 4 31B measured |
| LMArena Text: entertainment and media | 1405 | Not measured | Only Gemma 4 31B measured |
| LMArena Vision: English | 1271 | Not measured | Only Gemma 4 31B measured |
| LMArena Vision: Chinese | 1326 | Not measured | Only Gemma 4 31B measured |
| LMArena Vision: reading text | 1282 | Not measured | Only Gemma 4 31B measured |
| LMArena Vision: humor | 1280 | Not measured | Only Gemma 4 31B measured |
| LMArena Vision: captioning | 1218 | Not measured | Only Gemma 4 31B measured |
| LMArena Vision: recognizing things | 1226 | Not measured | Only Gemma 4 31B measured |
| LMArena Vision: creative writing | 1285 | Not measured | Only Gemma 4 31B measured |
| LMArena Document | 1425 | Not measured | Only Gemma 4 31B measured |
| Neither model has a result on the other 16 boards here | |||
Image generationNot comparablePublic boards, shown as published, kept out of the index0 boards, none shared
| Benchmark | Gemma 4 31B | 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
Gemma 4 31B costs less
Repository review
50K input + 3K output tokens
Gemma 4 31B costs less
Agent loop
200K input + 10K output tokens
Gemma 4 31B 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 | Google Gemma 4 31B | Mistral Mixtral 8x22B Instruct |
|---|---|---|
| Maker | Mistral AI | |
| Weights | Open weights | Open weights |
| Released | April 2, 2026 | April 17, 2024 |
| Context window | 262K | 66K |
| Input $/Mtok | $0.14 | $2.00 |
| Output $/Mtok | $0.40 | $6.00 |
| Coding index | 39.0 | Not benchmarked |
| Independent measurements behind it | 2 | 0 |
| Cost per solved task | Not computable | Not computable |
| Source | OpenRouter listing | OpenRouter listing |
Questions
Is Gemma 4 31B better than Mixtral 8x22B Instruct for coding?
Only Gemma 4 31B has a coding score, 39.0 on the Vibe Coding Index; Mixtral 8x22B Instruct has none, so the two cannot be ranked on coding. Compare them on price, context and the boards below.
Which is cheaper, Gemma 4 31B or Mixtral 8x22B Instruct?
Gemma 4 31B costs $0.14 per million input tokens and $0.40 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, Gemma 4 31B or Mixtral 8x22B Instruct?
Gemma 4 31B, with 262K tokens against 66K.
How many benchmarks is the Gemma 4 31B vs Mixtral 8x22B Instruct comparison based on?
5 benchmarks have a result for both models as of October 21, 2026. Gemma 4 31B's coding index rests on 2 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.