GPT-5.6 Sol Pro vs Mixtral 8x22B Instruct
Mixtral 8x22B Instruct costs 3.3x less per output token than GPT-5.6 Sol Pro ($6.00 vs $20.00 per million). Updated October 22, 2026; 1 benchmarks have a result for both.
GPT-5.6 Sol Pro or Mixtral 8x22B Instruct: which to pick
Neither model has a coding score yet, so the two cannot be ranked on coding.
Pick GPT-5.6 Sol Pro for a larger context window (1.05M against 66K tokens).
- Shared results
- 1
- GPT-5.6 Sol Pro only
- 6
- Mixtral 8x22B Instruct only
- 7
- Like-for-like categories
- 1 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
GPT-5.6 Sol Pro
GPT-5.6 Sol Pro takes 1.05M tokens against 66K.
Listed by OpenRouter
Everyday cost
1K input + 500 output tokens
Mixtral 8x22B Instruct
GPT-5.6 Sol Pro $0.014, Mixtral 8x22B Instruct $0.0050 per turn.
List prices
At a glance
- Coding index
- GPT-5.6 Sol Pro not benchmarked, Mixtral 8x22B Instruct not benchmarked.
- Widest category
- General, 40.9 points apart on average over 1 shared benchmark.
- Widest single gap
- DTBench: GPT-5.6 Sol Pro 96.0% against Mixtral 8x22B Instruct 55.1%, 40.9 points apart on a 0 to 100 scale.
- Output price
- GPT-5.6 Sol Pro $20.00 against Mixtral 8x22B Instruct $6.00 per million output tokens, 3.3x apart.
- Context window
- GPT-5.6 Sol Pro 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-5.6 Sol Pro | Bars | Mixtral 8x22B Instruct | Ties |
|---|---|---|---|---|
| General | 1 | 0 | ||
| All shared boards | 1 | 0 |
CodingDirectional onlySix of these boards feed the Vibe Coding Index3 boards, none shared
| Benchmark | GPT-5.6 Sol Pro | Mixtral 8x22B Instruct | Leader |
|---|---|---|---|
| LiveCodeBench (Artificial Analysis run) | Not measured | 14.8% | Only Mixtral 8x22B Instruct measured |
| WeirdML | 89.4% | Not measured | Only GPT-5.6 Sol Pro measured |
| SciCode | Not measured | 0.0% | Only Mixtral 8x22B Instruct measured |
| Neither model has a result on the other 36 boards here | |||
IntelligenceDirectional onlyPublic boards, shown as published, kept out of the index2 boards, none shared
| Benchmark | GPT-5.6 Sol Pro | Mixtral 8x22B Instruct | Leader |
|---|---|---|---|
| AA Intelligence Index | Not measured | 5.7 | Only Mixtral 8x22B Instruct measured |
| Epoch Capabilities Index | Not measured | 122.0 | Only Mixtral 8x22B Instruct measured |
Agentic workDirectional onlyPublic boards, shown as published, kept out of the index1 board, none shared
| Benchmark | GPT-5.6 Sol Pro | Mixtral 8x22B Instruct | Leader |
|---|---|---|---|
| APEX-Agents | 51.4% | Not measured | Only GPT-5.6 Sol Pro measured |
| Neither model has a result on the other 40 boards here | |||
ReasoningDirectional onlyPublic boards, shown as published, kept out of the index4 boards, none shared
| Benchmark | GPT-5.6 Sol Pro | 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 |
| SimpleBench | 71.7% | Not measured | Only GPT-5.6 Sol Pro measured |
| Chess puzzles | 68.0% | Not measured | Only GPT-5.6 Sol Pro measured |
| Neither model has a result on the other 18 boards here | |||
MathDirectional onlyPublic boards, shown as published, kept out of the index1 board, none shared
| Benchmark | GPT-5.6 Sol Pro | Mixtral 8x22B Instruct | Leader |
|---|---|---|---|
| FrontierMath, tier 4 | 80.5% | Not measured | Only GPT-5.6 Sol Pro measured |
| Neither model has a result on the other 12 boards here | |||
KnowledgeDirectional onlyPublic boards, shown as published, kept out of the index1 board, none shared
| Benchmark | GPT-5.6 Sol Pro | Mixtral 8x22B Instruct | Leader |
|---|---|---|---|
| MMLU Pro (Artificial Analysis run) | Not measured | 53.7% | Only Mixtral 8x22B Instruct 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 | GPT-5.6 Sol Pro | Mixtral 8x22B Instruct | Leader |
|---|---|---|---|
| Neither model has a result on 9 boards here | |||
GeneralLike-for-likePublic boards, shown as published, kept out of the index10
Image generationNot comparablePublic boards, shown as published, kept out of the index0 boards, none shared
| Benchmark | GPT-5.6 Sol Pro | 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
Mixtral 8x22B Instruct costs less
Repository review
50K input + 3K output tokens
Mixtral 8x22B Instruct costs less
Agent loop
200K input + 10K output tokens
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-5.6 Sol Pro | Mistral Mixtral 8x22B Instruct |
|---|---|---|
| Maker | OpenAI | Mistral AI |
| Weights | No public weights listed | Open weights |
| Released | July 9, 2026 | April 17, 2024 |
| Context window | 1.05M | 66K |
| Input $/Mtok | $4.00 | $2.00 |
| Output $/Mtok | $20.00 | $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 GPT-5.6 Sol Pro better than Mixtral 8x22B Instruct for coding?
Neither model has a coding score yet, so the two cannot be ranked on coding. Pick GPT-5.6 Sol Pro for a larger context window (1.05M against 66K tokens).
Which is cheaper, GPT-5.6 Sol Pro or Mixtral 8x22B Instruct?
GPT-5.6 Sol Pro costs $4.00 per million input tokens and $20.00 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-5.6 Sol Pro or Mixtral 8x22B Instruct?
GPT-5.6 Sol Pro, with 1.05M tokens against 66K.
How many benchmarks is the GPT-5.6 Sol Pro vs Mixtral 8x22B Instruct comparison based on?
1 benchmarks have a result for both models as of October 22, 2026. GPT-5.6 Sol Pro'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.