Mixtral 8x22B Instruct vs Qwen3.6 Flash
Updated October 21, 2026. 2 benchmarks have a result for both. Coding is ranked on the Vibe Coding Index; every other board is shown as published.
Decision reading
Neither model has a coding score yet, so the two cannot be ranked on coding.
Mixtral 8x22B Instruct has the edge where what matters is Epoch Capabilities Index or DTBench, where it leads.
- Shared results
- 2
- Mixtral 8x22B Instruct only
- 5
- Qwen3.6 Flash only
- 9
- Like-for-like categories
- 2 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
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
Qwen3.6 Flash
Qwen3.6 Flash takes 1M tokens against 66K.
Listed by OpenRouter
Everyday cost
1K input + 500 output tokens
Qwen3.6 Flash
Mixtral 8x22B Instruct $0.0050, Qwen3.6 Flash $0.0008 per turn.
List prices
At a glance
- Coding index
- Mixtral 8x22B Instruct not benchmarked, Qwen3.6 Flash not benchmarked.
- Widest category
- Intelligence, 26.1 points apart on average over 1 shared benchmark.
- Widest single gap
- Epoch Capabilities Index: Mixtral 8x22B Instruct 122.0 against Qwen3.6 Flash 142.9, 26.1 points apart on a 0 to 100 scale.
- Output price
- Mixtral 8x22B Instruct $6.00 against Qwen3.6 Flash $1.125 per million output tokens, 5.3x apart.
- Context window
- Mixtral 8x22B Instruct takes 66K tokens, Qwen3.6 Flash 1M.
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 | Mixtral 8x22B Instruct | Bars | Qwen3.6 Flash | 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 | Mixtral 8x22B Instruct | Qwen3.6 Flash | Leader |
|---|---|---|---|
| LiveCodeBench (Artificial Analysis run) | 14.8% | Not measured | Only Mixtral 8x22B Instruct measured |
| ALE-Bench | Not measured | 326.4 | Only Qwen3.6 Flash measured |
| Neither model has a result on the other 36 boards here | |||
IntelligenceLike-for-likePublic boards, shown as published, kept out of the index01
| Benchmark | Mixtral 8x22B Instruct | Qwen3.6 Flash | Leader |
|---|---|---|---|
| AA Intelligence Index | 5.7 | Not measured | Only Mixtral 8x22B Instruct measured |
| Epoch Capabilities Index | 122.0 | 142.9 | Qwen3.6 Flash |
Agentic workNot comparablePublic boards, shown as published, kept out of the index0 boards, none shared
| Benchmark | Mixtral 8x22B Instruct | Qwen3.6 Flash | Leader |
|---|---|---|---|
| Neither model has a result on 39 boards here | |||
ReasoningDirectional onlyPublic boards, shown as published, kept out of the index6 boards, none shared
| Benchmark | Mixtral 8x22B Instruct | Qwen3.6 Flash | Leader |
|---|---|---|---|
| GPQA Diamond (Artificial Analysis run) | 33.2% | Not measured | Only Mixtral 8x22B Instruct measured |
| Humanity's Last Exam (Artificial Analysis run) | 4.0% | Not measured | Only Mixtral 8x22B Instruct measured |
| GPQA Diamond (Epoch AI run) | Not measured | 83.3% | Only Qwen3.6 Flash measured |
| SimpleBench | Not measured | 35.2% | Only Qwen3.6 Flash measured |
| Chess puzzles | Not measured | 12.0% | Only Qwen3.6 Flash measured |
| Mystery game puzzles | Not measured | 18.0% | Only Qwen3.6 Flash measured |
| Neither model has a result on the other 15 boards here | |||
MathDirectional onlyPublic boards, shown as published, kept out of the index2 boards, none shared
| Benchmark | Mixtral 8x22B Instruct | Qwen3.6 Flash | Leader |
|---|---|---|---|
| OTIS Mock AIME | Not measured | 84.4% | Only Qwen3.6 Flash measured |
| FrontierMath, tiers 1 to 3 | Not measured | 22.5% | Only Qwen3.6 Flash measured |
| Neither model has a result on the other 11 boards here | |||
KnowledgeDirectional onlyPublic boards, shown as published, kept out of the index2 boards, none shared
| Benchmark | Mixtral 8x22B Instruct | Qwen3.6 Flash | Leader |
|---|---|---|---|
| MMLU Pro (Artificial Analysis run) | 53.7% | Not measured | Only Mixtral 8x22B Instruct measured |
| SimpleQA Verified | Not measured | 15.9% | Only Qwen3.6 Flash measured |
| Neither model has a result on the other 15 boards here | |||
Web designNot comparablePublic boards, shown as published, kept out of the index0 boards, none shared
| Benchmark | Mixtral 8x22B Instruct | Qwen3.6 Flash | Leader |
|---|---|---|---|
| Neither model has a result on 9 boards here | |||
GeneralLike-for-likePublic boards, shown as published, kept out of the index01
Image generationNot comparablePublic boards, shown as published, kept out of the index0 boards, none shared
| Benchmark | Mixtral 8x22B Instruct | Qwen3.6 Flash | 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
Qwen3.6 Flash costs less
Repository review
50K input + 3K output tokens
Qwen3.6 Flash costs less
Agent loop
200K input + 10K output tokens
Qwen3.6 Flash 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 Mixtral 8x22B Instruct | Qwen3.6 Flash |
|---|---|---|
| Maker | Mistral AI | Qwen |
| Weights | Open weights | No public weights listed |
| Released | April 17, 2024 | April 27, 2026 |
| Context window | 66K | 1M |
| Input $/Mtok | $2.00 | $0.1875 |
| Output $/Mtok | $6.00 | $1.125 |
| 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 Mixtral 8x22B Instruct better than Qwen3.6 Flash for coding?
Neither model has a coding score yet, so the two cannot be ranked on coding. Mixtral 8x22B Instruct has the edge where what matters is Epoch Capabilities Index or DTBench, where it leads.
Which is cheaper, Mixtral 8x22B Instruct or Qwen3.6 Flash?
Mixtral 8x22B Instruct costs $2.00 per million input tokens and $6.00 per million output tokens; Qwen3.6 Flash costs $0.1875 and $1.125. Cost per solved task is known for neither of them.
Which has the bigger context window, Mixtral 8x22B Instruct or Qwen3.6 Flash?
Qwen3.6 Flash, with 1M tokens against 66K.
How many benchmarks is the Mixtral 8x22B Instruct vs Qwen3.6 Flash comparison based on?
2 benchmarks have a result for both models as of October 21, 2026. Mixtral 8x22B Instruct's coding index rests on 0 independent benchmarks and Qwen3.6 Flash's on 0. Where only one model has a result, the page says so instead of naming a winner.