Trinity Large Thinking vs Mixtral 8x22B Instruct
Updated October 21, 2026. 3 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.
Trinity Large Thinking has the edge where output tokens cost 7.5x less, and where the context window is larger, 262K against 66K tokens.
- Shared results
- 3
- Trinity Large Thinking only
- 49
- Mixtral 8x22B Instruct only
- 4
- 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
Trinity Large Thinking
Trinity Large Thinking leads, 10.8 against 5.7.
Same board, both measured
Agentic work
AA Agentic Index
No call
Only Trinity Large Thinking has a AA Agentic Index result, 1.0.
Directional only
Web design
Design Arena: websites
No call
Only Trinity Large Thinking has a Design Arena: websites result, 1137.
Directional only
Long documents
Listed context window
Trinity Large Thinking
Trinity Large Thinking takes 262K tokens against 66K.
Listed by OpenRouter
Everyday cost
1K input + 500 output tokens
Trinity Large Thinking
Trinity Large Thinking $0.0006, Mixtral 8x22B Instruct $0.0050 per turn.
List prices
At a glance
- Coding index
- Trinity Large Thinking not benchmarked, Mixtral 8x22B Instruct not benchmarked.
- Widest category
- Reasoning, 26.9 points apart on average over 2 shared benchmarks.
- Widest single gap
- GPQA Diamond (Artificial Analysis run): Trinity Large Thinking 75.2% against Mixtral 8x22B Instruct 33.2%, 42.0 points apart on a 0 to 100 scale.
- Output price
- Trinity Large Thinking $0.80 against Mixtral 8x22B Instruct $6.00 per million output tokens, 7.5x apart.
- Context window
- Trinity Large Thinking 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 | Trinity Large Thinking | Bars | Mixtral 8x22B Instruct | Ties |
|---|---|---|---|---|
| Intelligence | 1 | 0 | ||
| Reasoning | 2 | 0 | ||
| All shared boards | 3 | 0 |
CodingDirectional onlySix of these boards feed the Vibe Coding Index9 boards, none shared
| Benchmark | Trinity Large Thinking | Mixtral 8x22B Instruct | Leader |
|---|---|---|---|
| LMArena WebDev | 1238 | Not measured | Only Trinity Large Thinking measured |
| AA Coding Index | 25.8 | Not measured | Only Trinity Large Thinking measured |
| LiveCodeBench (Artificial Analysis run) | Not measured | 14.8% | Only Mixtral 8x22B Instruct measured |
| SciCode | 40.6% | Not measured | Only Trinity Large Thinking measured |
| Terminal-Bench Hard (Artificial Analysis run) | 22.7% | Not measured | Only Trinity Large Thinking measured |
| LMArena Text: coding | 1357 | Not measured | Only Trinity Large Thinking measured |
| LMArena Text: software and IT | 1362 | Not measured | Only Trinity Large Thinking measured |
| LMArena WebDev: React | 1231 | Not measured | Only Trinity Large Thinking measured |
| LMArena WebDev: HTML | 1240 | Not measured | Only Trinity Large Thinking measured |
| Neither model has a result on the other 29 boards here | |||
IntelligenceLike-for-likePublic boards, shown as published, kept out of the index10
| Benchmark | Trinity Large Thinking | Mixtral 8x22B Instruct | Leader |
|---|---|---|---|
| AA Intelligence Index | 10.8 | 5.7 | Trinity Large Thinking |
| Epoch Capabilities Index | Not measured | 122.0 | Only Mixtral 8x22B Instruct measured |
Agentic workDirectional onlyPublic boards, shown as published, kept out of the index2 boards, none shared
| Benchmark | Trinity Large Thinking | Mixtral 8x22B Instruct | Leader |
|---|---|---|---|
| AA Agentic Index | 1.0 | Not measured | Only Trinity Large Thinking measured |
| τ²-Bench Telecom | 90.1% | Not measured | Only Trinity Large Thinking measured |
| Neither model has a result on the other 37 boards here | |||
ReasoningLike-for-likePublic boards, shown as published, kept out of the index20
| Benchmark | Trinity Large Thinking | Mixtral 8x22B Instruct | Leader |
|---|---|---|---|
| GPQA Diamond (Artificial Analysis run) | 75.2% | 33.2% | Trinity Large Thinking |
| Humanity's Last Exam (Artificial Analysis run) | 15.8% | 4.0% | Trinity Large Thinking |
| LMArena Text: hard prompts | 1342 | Not measured | Only Trinity Large Thinking measured |
| LMArena Text: expert | 1359 | Not measured | Only Trinity Large Thinking measured |
| LMArena Text: hard prompts in English | 1356 | Not measured | Only Trinity Large Thinking measured |
| Neither model has a result on the other 16 boards here | |||
MathDirectional onlyPublic boards, shown as published, kept out of the index2 boards, none shared
| Benchmark | Trinity Large Thinking | Mixtral 8x22B Instruct | Leader |
|---|---|---|---|
| LMArena Text: math | 1365 | Not measured | Only Trinity Large Thinking measured |
| LMArena Text: mathematical work | 1350 | Not measured | Only Trinity Large Thinking measured |
| Neither model has a result on the other 11 boards here | |||
KnowledgeDirectional onlyPublic boards, shown as published, kept out of the index7 boards, none shared
| Benchmark | Trinity Large Thinking | Mixtral 8x22B Instruct | Leader |
|---|---|---|---|
| CaseLaw (Vals AI) | 57.9% | Not measured | Only Trinity Large Thinking measured |
| CorpFin (Vals AI) | 54.7% | Not measured | Only Trinity Large Thinking measured |
| MMLU Pro (Artificial Analysis run) | Not measured | 53.7% | Only Mixtral 8x22B Instruct measured |
| LMArena Text: science | 1355 | Not measured | Only Trinity Large Thinking measured |
| LMArena Text: medicine and healthcare | 1349 | Not measured | Only Trinity Large Thinking measured |
| LMArena Text: legal and government | 1345 | Not measured | Only Trinity Large Thinking measured |
| LMArena Text: business and finance | 1329 | Not measured | Only Trinity Large Thinking measured |
| Neither model has a result on the other 10 boards here | |||
Web designDirectional onlyPublic boards, shown as published, kept out of the index8 boards, none shared
| Benchmark | Trinity Large Thinking | Mixtral 8x22B Instruct | Leader |
|---|---|---|---|
| Design Arena: websites | 1137 | Not measured | Only Trinity Large Thinking measured |
| Design Arena: UI components | 1045 | Not measured | Only Trinity Large Thinking measured |
| Design Arena: game dev | 1079 | Not measured | Only Trinity Large Thinking measured |
| Design Arena: data viz | 1098 | Not measured | Only Trinity Large Thinking measured |
| Design Arena: 3D | 1082 | Not measured | Only Trinity Large Thinking measured |
| Design Arena: all code categories | 1117 | Not measured | Only Trinity Large Thinking measured |
| Design Arena: SVG | 1017 | Not measured | Only Trinity Large Thinking measured |
| Design Arena: ASCII art | 1041 | Not measured | Only Trinity Large Thinking measured |
| Neither model has a result on the other 1 board here | |||
GeneralDirectional onlyPublic boards, shown as published, kept out of the index21 boards, none shared
| Benchmark | Trinity Large Thinking | Mixtral 8x22B Instruct | Leader |
|---|---|---|---|
| IFBench | 56.3% | Not measured | Only Trinity Large Thinking measured |
| Long context reasoning (AA-LCR) | 38.0% | Not measured | Only Trinity Large Thinking measured |
| DTBench | Not measured | 55.1% | Only Mixtral 8x22B Instruct measured |
| Surface Evolver Bench | 15.6% | Not measured | Only Trinity Large Thinking measured |
| LMArena Text | 1340 | Not measured | Only Trinity Large Thinking measured |
| LMArena Text: instruction following | 1326 | Not measured | Only Trinity Large Thinking measured |
| LMArena Text: creative writing | 1308 | Not measured | Only Trinity Large Thinking measured |
| LMArena Text: English | 1356 | Not measured | Only Trinity Large Thinking measured |
| LMArena Text: non-English | 1325 | Not measured | Only Trinity Large Thinking measured |
| LMArena Text: Chinese | 1371 | Not measured | Only Trinity Large Thinking measured |
| LMArena Text: German | 1356 | Not measured | Only Trinity Large Thinking measured |
| LMArena Text: Japanese | 1312 | Not measured | Only Trinity Large Thinking measured |
| LMArena Text: Korean | 1306 | Not measured | Only Trinity Large Thinking measured |
| LMArena Text: French | 1366 | Not measured | Only Trinity Large Thinking measured |
| LMArena Text: Spanish | 1327 | Not measured | Only Trinity Large Thinking measured |
| LMArena Text: Russian | 1338 | Not measured | Only Trinity Large Thinking measured |
| LMArena Text: Polish | 1312 | Not measured | Only Trinity Large Thinking measured |
| LMArena Text: multi-turn | 1320 | Not measured | Only Trinity Large Thinking measured |
| LMArena Text: longer queries | 1318 | Not measured | Only Trinity Large Thinking measured |
| LMArena Text: writing and language | 1317 | Not measured | Only Trinity Large Thinking measured |
| LMArena Text: entertainment and media | 1296 | Not measured | Only Trinity Large Thinking measured |
| Neither model has a result on the other 25 boards here | |||
Image generationNot comparablePublic boards, shown as published, kept out of the index0 boards, none shared
| Benchmark | Trinity Large Thinking | 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
Trinity Large Thinking costs less
Repository review
50K input + 3K output tokens
Trinity Large Thinking costs less
Agent loop
200K input + 10K output tokens
Trinity Large Thinking 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 | Arcee AI Trinity Large Thinking | Mistral Mixtral 8x22B Instruct |
|---|---|---|
| Maker | Arcee AI | Mistral AI |
| Weights | Open weights | Open weights |
| Released | April 1, 2026 | April 17, 2024 |
| Context window | 262K | 66K |
| Input $/Mtok | $0.25 | $2.00 |
| Output $/Mtok | $0.80 | $6.00 |
| Coding index | Not benchmarked | Not benchmarked |
| Independent measurements behind it | 1 | 0 |
| Cost per solved task | Not computable | Not computable |
| Source | OpenRouter listing | OpenRouter listing |
Questions
Is Trinity Large Thinking better than Mixtral 8x22B Instruct for coding?
Neither model has a coding score yet, so the two cannot be ranked on coding. Trinity Large Thinking has the edge where output tokens cost 7.5x less, and where the context window is larger, 262K against 66K tokens.
Which is cheaper, Trinity Large Thinking or Mixtral 8x22B Instruct?
Trinity Large Thinking costs $0.25 per million input tokens and $0.80 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, Trinity Large Thinking or Mixtral 8x22B Instruct?
Trinity Large Thinking, with 262K tokens against 66K.
How many benchmarks is the Trinity Large Thinking vs Mixtral 8x22B Instruct comparison based on?
3 benchmarks have a result for both models as of October 21, 2026. Trinity Large Thinking's coding index rests on 1 independent benchmark and Mixtral 8x22B Instruct's on 0. Where only one model has a result, the page says so instead of naming a winner.