GPT-6.1 Sol vs Mixtral 8x22B Instruct
Updated October 21, 2026. 4 benchmarks have a result for both. Coding is ranked on the Vibe Coding Index; every other board is shown as published.
vs boards won of 4 shared
Decision reading
Only GPT-6.1 Sol has a coding score, 82.4 on the Vibe Coding Index; Mixtral 8x22B Instruct has none, so the two cannot be ranked on coding.
Mixtral 8x22B Instruct has the edge where output tokens cost 1.7x less.
Model AGPT-6.1 SolOpenAI82.4/1005 independent benchmarksNo cost per solved taskModel BMixtral 8x22B InstructMistral AINot benchmarkedNo coding benchmarkNo cost per solved task
- Shared results
- 4
- GPT-6.1 Sol only
- 91
- Mixtral 8x22B Instruct only
- 3
- Like-for-like categories
- 3 of 9
Shared results can support a head-to-head reading. Results only one model has describe coverage, not superiority.
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 GPT-6.1 Sol has a coding score, so no call is made.
One side not measured
Intelligence
AA Intelligence Index
GPT-6.1 Sol
GPT-6.1 Sol leads, 51.8 against 5.7.
Same board, both measured
Web design
Design Arena: websites
No call
Only GPT-6.1 Sol has a Design Arena: websites result, 1320.
Directional only
General
Vals Index
No call
Only GPT-6.1 Sol has a Vals Index result, 63.9%.
Directional only
Long documents
Listed context window
GPT-6.1 Sol
GPT-6.1 Sol takes 1.05M tokens against 66K.
Listed by OpenRouter
Everyday cost
1K input + 500 output tokens
Mixtral 8x22B Instruct
GPT-6.1 Sol $0.0070, Mixtral 8x22B Instruct $0.0050 per turn.
List prices
At a glance
- Coding index
- GPT-6.1 Sol 82.4 from 5 benchmarks, Mixtral 8x22B Instruct not benchmarked.
- Widest category
- Intelligence, 52.0 points apart on average over 2 shared benchmarks.
- Widest single gap
- Epoch Capabilities Index: GPT-6.1 Sol 168.4 against Mixtral 8x22B Instruct 122.0, 57.9 points apart on a 0 to 100 scale.
- Output price
- GPT-6.1 Sol $10.00 against Mixtral 8x22B Instruct $6.00 per million output tokens, 1.7x apart.
- Context window
- GPT-6.1 Sol takes 1.05M 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 | GPT-6.1 Sol | Bars | Mixtral 8x22B Instruct | Ties |
|---|---|---|---|---|
| Intelligence | 2 | 0 | ||
| Reasoning | 1 | 0 | ||
| General | 1 | 0 | ||
| All shared boards | 4 | 0 |
CodingDirectional onlySix of these boards feed the Vibe Coding Index18 boards, none shared
| Benchmark | GPT-6.1 Sol | Mixtral 8x22B Instruct | Leader |
|---|---|---|---|
| LiveBench coding | 96.0% | Not measured | Only GPT-6.1 Sol measured |
| LMArena WebDev | 1753 | Not measured | Only GPT-6.1 Sol measured |
| Terminal-Bench 4 (Vals AI) | 55.0% | Not measured | Only GPT-6.1 Sol measured |
| Vibe Code Bench (Vals AI) | 88.9% | Not measured | Only GPT-6.1 Sol measured |
| Code migration (Vals AI) | 65.1% | Not measured | Only GPT-6.1 Sol measured |
| ProgramBench (Vals AI) | 3.0% | Not measured | Only GPT-6.1 Sol measured |
| IOI (Vals AI) | 96.9% | Not measured | Only GPT-6.1 Sol measured |
| SWE-bench Multimodal (Vals AI) | 43.5% | Not measured | Only GPT-6.1 Sol measured |
| CyberBench (Vals AI) | 39.3% | Not measured | Only GPT-6.1 Sol measured |
| LiveCodeBench (Artificial Analysis run) | Not measured | 14.8% | Only Mixtral 8x22B Instruct measured |
| SciCode | 55.8% | Not measured | Only GPT-6.1 Sol measured |
| FrontierCode | 50.2% | Not measured | Only GPT-6.1 Sol measured |
| ALE-Bench | 2743.8 | Not measured | Only GPT-6.1 Sol measured |
| LMArena Text: coding | 1478 | Not measured | Only GPT-6.1 Sol measured |
| LMArena Text: software and IT | 1476 | Not measured | Only GPT-6.1 Sol measured |
| LMArena WebDev: React | 1754 | Not measured | Only GPT-6.1 Sol measured |
| LMArena WebDev: HTML | 1800 | Not measured | Only GPT-6.1 Sol measured |
| LMArena WebDev: from an image | 1702 | Not measured | Only GPT-6.1 Sol measured |
| Neither model has a result on the other 20 boards here | |||
IntelligenceLike-for-likePublic boards, shown as published, kept out of the index20
| Benchmark | GPT-6.1 Sol | Mixtral 8x22B Instruct | Leader |
|---|---|---|---|
| AA Intelligence Index | 51.8 | 5.7 | GPT-6.1 Sol |
| Epoch Capabilities Index | 168.4 | 122.0 | GPT-6.1 Sol |
Agentic workDirectional onlyPublic boards, shown as published, kept out of the index17 boards, none shared
| Benchmark | GPT-6.1 Sol | Mixtral 8x22B Instruct | Leader |
|---|---|---|---|
| Design Arena: agents building mobile apps | 1200 | Not measured | Only GPT-6.1 Sol measured |
| Design Arena: spreadsheets | 1244 | Not measured | Only GPT-6.1 Sol measured |
| LiveBench research | 83.5% | Not measured | Only GPT-6.1 Sol measured |
| LiveBench browser | 88.0% | Not measured | Only GPT-6.1 Sol measured |
| LiveBench long agentic | 73.0% | Not measured | Only GPT-6.1 Sol measured |
| SREBench (Vals AI) | 50.8% | Not measured | Only GPT-6.1 Sol measured |
| Finance Agent (Vals AI) | 52.0% | Not measured | Only GPT-6.1 Sol measured |
| Tax Agent Bench (Vals AI) | 21.8% | Not measured | Only GPT-6.1 Sol measured |
| Legal Research Bench (Vals AI) | 38.5% | Not measured | Only GPT-6.1 Sol measured |
| Harvey's Legal Agent Benchmark (Vals AI) | 6.3% | Not measured | Only GPT-6.1 Sol measured |
| Excel Modeling Benchmark (Vals AI) | 70.8% | Not measured | Only GPT-6.1 Sol measured |
| BioMysteryBench (Vals AI) | 79.6% | Not measured | Only GPT-6.1 Sol measured |
| Terminal-Bench-Science (Vals AI) | 52.9% | Not measured | Only GPT-6.1 Sol measured |
| Vals Science Index | 59.6% | Not measured | Only GPT-6.1 Sol measured |
| Robo-bench (Vals AI) | 28.3% | Not measured | Only GPT-6.1 Sol measured |
| APEX-Agents | 60.0% | Not measured | Only GPT-6.1 Sol measured |
| SpireClimb | 24.7% | Not measured | Only GPT-6.1 Sol measured |
| Neither model has a result on the other 22 boards here | |||
ReasoningLike-for-likePublic boards, shown as published, kept out of the index10
| Benchmark | GPT-6.1 Sol | Mixtral 8x22B Instruct | Leader |
|---|---|---|---|
| LiveBench reasoning | 92.6% | Not measured | Only GPT-6.1 Sol measured |
| MysteryMechanism (Vals AI) | 46.4% | Not measured | Only GPT-6.1 Sol measured |
| GPQA Diamond (Artificial Analysis run) | Not measured | 33.2% | Only Mixtral 8x22B Instruct measured |
| Humanity's Last Exam (Artificial Analysis run) | 52.9% | 4.0% | GPT-6.1 Sol |
| GPQA Diamond (Epoch AI run) | 95.4% | Not measured | Only GPT-6.1 Sol measured |
| ARC-AGI | 98.5% | Not measured | Only GPT-6.1 Sol measured |
| ARC-AGI-2 | 94.2% | Not measured | Only GPT-6.1 Sol measured |
| Chess puzzles | 68.0% | Not measured | Only GPT-6.1 Sol measured |
| Mystery game puzzles | 80.0% | Not measured | Only GPT-6.1 Sol measured |
| EBR-bench | 54.3% | Not measured | Only GPT-6.1 Sol measured |
| LMArena Text: hard prompts | 1463 | Not measured | Only GPT-6.1 Sol measured |
| LMArena Text: expert | 1489 | Not measured | Only GPT-6.1 Sol measured |
| LMArena Text: hard prompts in English | 1465 | Not measured | Only GPT-6.1 Sol measured |
| LMArena Vision: diagrams | 1306 | Not measured | Only GPT-6.1 Sol measured |
| LMArena Vision: homework | 1356 | Not measured | Only GPT-6.1 Sol measured |
| Neither model has a result on the other 6 boards here | |||
MathDirectional onlyPublic boards, shown as published, kept out of the index6 boards, none shared
| Benchmark | GPT-6.1 Sol | Mixtral 8x22B Instruct | Leader |
|---|---|---|---|
| OTIS Mock AIME | 100.0% | Not measured | Only GPT-6.1 Sol measured |
| FrontierMath, tiers 1 to 3 | 93.7% | Not measured | Only GPT-6.1 Sol measured |
| FrontierMath, tier 4 | 100.0% | Not measured | Only GPT-6.1 Sol measured |
| ProofBench | 99.0% | Not measured | Only GPT-6.1 Sol measured |
| LMArena Text: math | 1489 | Not measured | Only GPT-6.1 Sol measured |
| LMArena Text: mathematical work | 1513 | Not measured | Only GPT-6.1 Sol measured |
| Neither model has a result on the other 7 boards here | |||
KnowledgeDirectional onlyPublic boards, shown as published, kept out of the index7 boards, none shared
| Benchmark | GPT-6.1 Sol | Mixtral 8x22B Instruct | Leader |
|---|---|---|---|
| MedCode (Vals AI) | 48.8% | Not measured | Only GPT-6.1 Sol measured |
| MMLU Pro (Artificial Analysis run) | Not measured | 53.7% | Only Mixtral 8x22B Instruct measured |
| SimpleQA Verified | 73.9% | Not measured | Only GPT-6.1 Sol measured |
| LMArena Text: science | 1444 | Not measured | Only GPT-6.1 Sol measured |
| LMArena Text: medicine and healthcare | 1433 | Not measured | Only GPT-6.1 Sol measured |
| LMArena Text: legal and government | 1471 | Not measured | Only GPT-6.1 Sol measured |
| LMArena Text: business and finance | 1445 | Not measured | Only GPT-6.1 Sol measured |
| Neither model has a result on the other 10 boards here | |||
Web designDirectional onlyPublic boards, shown as published, kept out of the index7 boards, none shared
| Benchmark | GPT-6.1 Sol | Mixtral 8x22B Instruct | Leader |
|---|---|---|---|
| Design Arena: websites | 1320 | Not measured | Only GPT-6.1 Sol measured |
| Design Arena: UI components | 1330 | Not measured | Only GPT-6.1 Sol measured |
| Design Arena: game dev | 1389 | Not measured | Only GPT-6.1 Sol measured |
| Design Arena: data viz | 1280 | Not measured | Only GPT-6.1 Sol measured |
| Design Arena: 3D | 1463 | Not measured | Only GPT-6.1 Sol measured |
| Design Arena: all code categories | 1345 | Not measured | Only GPT-6.1 Sol measured |
| LiveBench design | 82.1% | Not measured | Only GPT-6.1 Sol measured |
| Neither model has a result on the other 2 boards here | |||
GeneralLike-for-likePublic boards, shown as published, kept out of the index10
| Benchmark | GPT-6.1 Sol | Mixtral 8x22B Instruct | Leader |
|---|---|---|---|
| Vals Index | 63.9% | Not measured | Only GPT-6.1 Sol measured |
| LiveBench data analysis | 82.7% | Not measured | Only GPT-6.1 Sol measured |
| Public Benefits Bench (Vals AI) | 59.3% | Not measured | Only GPT-6.1 Sol measured |
| SAGE (Vals AI) | 46.5% | Not measured | Only GPT-6.1 Sol measured |
| MedScribe (Vals AI) | 86.5% | Not measured | Only GPT-6.1 Sol measured |
| Long context reasoning (AA-LCR) | 84.0% | Not measured | Only GPT-6.1 Sol measured |
| DTBench | 96.5% | 55.1% | GPT-6.1 Sol |
| LMCA | 62.8% | Not measured | Only GPT-6.1 Sol measured |
| Furniture assembly | 80.0% | Not measured | Only GPT-6.1 Sol measured |
| LMArena Text | 1443 | Not measured | Only GPT-6.1 Sol measured |
| LMArena Text: instruction following | 1466 | Not measured | Only GPT-6.1 Sol measured |
| LMArena Text: creative writing | 1425 | Not measured | Only GPT-6.1 Sol measured |
| LMArena Vision | 1288 | Not measured | Only GPT-6.1 Sol measured |
| LMArena Text: English | 1450 | Not measured | Only GPT-6.1 Sol measured |
| LMArena Text: non-English | 1433 | Not measured | Only GPT-6.1 Sol measured |
| LMArena Text: Chinese | 1487 | Not measured | Only GPT-6.1 Sol measured |
| LMArena Text: French | 1460 | Not measured | Only GPT-6.1 Sol measured |
| LMArena Text: Spanish | 1439 | Not measured | Only GPT-6.1 Sol measured |
| LMArena Text: Russian | 1457 | Not measured | Only GPT-6.1 Sol measured |
| LMArena Text: multi-turn | 1442 | Not measured | Only GPT-6.1 Sol measured |
| LMArena Text: longer queries | 1458 | Not measured | Only GPT-6.1 Sol measured |
| LMArena Text: writing and language | 1444 | Not measured | Only GPT-6.1 Sol measured |
| LMArena Text: entertainment and media | 1426 | Not measured | Only GPT-6.1 Sol measured |
| LMArena Vision: English | 1274 | Not measured | Only GPT-6.1 Sol measured |
| LMArena Vision: reading text | 1289 | Not measured | Only GPT-6.1 Sol measured |
| LMArena Vision: creative writing | 1301 | Not measured | Only GPT-6.1 Sol measured |
| Neither model has a result on the other 20 boards here | |||
Image generationNot comparablePublic boards, shown as published, kept out of the index0 boards, none shared
| Benchmark | GPT-6.1 Sol | 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
GPT-6.1 Sol$0.0070Fits in one request
Mixtral 8x22B Instruct$0.0050Fits in one request
Mixtral 8x22B Instruct costs less
Repository review
50K input + 3K output tokens
GPT-6.1 Sol$0.130Fits in one request
Mixtral 8x22B Instruct$0.118Fits in one request
Mixtral 8x22B Instruct costs less
Agent loop
200K input + 10K output tokens
GPT-6.1 Sol$0.500Fits in one request
Mixtral 8x22B Instruct$0.460Exceeds the context window
Mixtral 8x22B Instruct 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-6.1 Sol | Mistral Mixtral 8x22B Instruct |
|---|---|---|
| Maker | OpenAI | Mistral AI |
| Weights | No public weights listed | Open weights |
| Released | September 29, 2026 | April 17, 2024 |
| Context window | 1.05M | 66K |
| Input $/Mtok | $2.00 | $2.00 |
| Output $/Mtok | $10.00 | $6.00 |
| Coding index | 82.4 | Not benchmarked |
| Independent measurements behind it | 5 | 0 |
| Cost per solved task | Not computable | Not computable |
| Source | OpenRouter listing | OpenRouter listing |
Questions
Is GPT-6.1 Sol better than Mixtral 8x22B Instruct for coding?
Only GPT-6.1 Sol has a coding score, 82.4 on the Vibe Coding Index; Mixtral 8x22B Instruct has none, so the two cannot be ranked on coding. Mixtral 8x22B Instruct has the edge where output tokens cost 1.7x less.
Which is cheaper, GPT-6.1 Sol or Mixtral 8x22B Instruct?
GPT-6.1 Sol costs $2.00 per million input tokens and $10.00 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, GPT-6.1 Sol or Mixtral 8x22B Instruct?
GPT-6.1 Sol, with 1.05M tokens against 66K.
How many benchmarks is the GPT-6.1 Sol vs Mixtral 8x22B Instruct comparison based on?
4 benchmarks have a result for both models as of October 21, 2026. GPT-6.1 Sol's coding index rests on 5 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.