Mercury 2.5 vs Mixtral 8x22B Instruct
Mercury 2.5 leads Mixtral 8x22B Instruct on the Artificial Analysis Intelligence Index, 12.3 to 5.7, and Mercury 2.5 costs 40.0x less per output token ($0.15 vs $6.00 per million). Updated October 21, 2026; 2 benchmarks have a result for both.
Mercury 2.5 or Mixtral 8x22B Instruct: which to pick
Only Mercury 2.5 has a coding score, 1.6 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
- 2
- Mercury 2.5 only
- 20
- Mixtral 8x22B Instruct only
- 6
- Like-for-like categories
- 2 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 Mercury 2.5 has a coding score, so no call is made.
One side not measured
Intelligence
AA Intelligence Index
Mercury 2.5
Mercury 2.5 leads, 12.3 against 5.7.
Same board, both measured
Long documents
Listed context window
Mercury 2.5
Mercury 2.5 takes 260K tokens against 66K.
Listed by OpenRouter
Everyday cost
1K input + 500 output tokens
Mercury 2.5
Mercury 2.5 $0.0001, Mixtral 8x22B Instruct $0.0050 per turn.
List prices
At a glance
- Coding index
- Mercury 2.5 1.6 from 2 benchmarks, Mixtral 8x22B Instruct not benchmarked.
- Widest category
- Reasoning, 7.8 points apart on average over 1 shared benchmark.
- Widest single gap
- Humanity's Last Exam (Artificial Analysis run): Mercury 2.5 11.8% against Mixtral 8x22B Instruct 4.0%, 7.8 points apart on a 0 to 100 scale.
- Output price
- Mercury 2.5 $0.15 against Mixtral 8x22B Instruct $6.00 per million output tokens, 40.0x apart.
- Context window
- Mercury 2.5 takes 260K 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 | Mercury 2.5 | Bars | Mixtral 8x22B Instruct | Ties |
|---|---|---|---|---|
| Intelligence | 1 | 0 | ||
| Reasoning | 1 | 0 | ||
| All shared boards | 2 | 0 |
CodingDirectional onlySix of these boards feed the Vibe Coding Index11 boards, none shared
| Benchmark | Mercury 2.5 | Mixtral 8x22B Instruct | Leader |
|---|---|---|---|
| Terminal-Bench 4 (Vals AI) | 0.0% | Not measured | Only Mercury 2.5 measured |
| Vibe Code Bench (Vals AI) | 3.7% | Not measured | Only Mercury 2.5 measured |
| Code migration (Vals AI) | 4.5% | Not measured | Only Mercury 2.5 measured |
| IOI (Vals AI) | 2.4% | Not measured | Only Mercury 2.5 measured |
| Terminal-Bench 2.1 (Vals AI) | 34.5% | Not measured | Only Mercury 2.5 measured |
| SkillsBench (Vals AI) | 18.1% | Not measured | Only Mercury 2.5 measured |
| CyberBench (Vals AI) | 45.5% | Not measured | Only Mercury 2.5 measured |
| LiveCodeBench (Artificial Analysis run) | Not measured | 14.8% | Only Mixtral 8x22B Instruct measured |
| SciCode | 38.5% | Not measured | Only Mercury 2.5 measured |
| ALE-Bench | 301.6 | Not measured | Only Mercury 2.5 measured |
| SciCode | Not measured | 0.0% | Only Mixtral 8x22B Instruct measured |
| Neither model has a result on the other 28 boards here | |||
IntelligenceLike-for-likePublic boards, shown as published, kept out of the index10
| Benchmark | Mercury 2.5 | Mixtral 8x22B Instruct | Leader |
|---|---|---|---|
| AA Intelligence Index | 12.3 | 5.7 | Mercury 2.5 |
| Epoch Capabilities Index | Not measured | 122.0 | Only Mixtral 8x22B Instruct measured |
Agentic workDirectional onlyPublic boards, shown as published, kept out of the index5 boards, none shared
| Benchmark | Mercury 2.5 | Mixtral 8x22B Instruct | Leader |
|---|---|---|---|
| Finance Agent (Vals AI) | 18.9% | Not measured | Only Mercury 2.5 measured |
| Tax Agent Bench (Vals AI) | 2.5% | Not measured | Only Mercury 2.5 measured |
| Legal Research Bench (Vals AI) | 4.3% | Not measured | Only Mercury 2.5 measured |
| Excel Modeling Benchmark (Vals AI) | 8.8% | Not measured | Only Mercury 2.5 measured |
| Terminal-Bench-Science (Vals AI) | 0.0% | Not measured | Only Mercury 2.5 measured |
| Neither model has a result on the other 36 boards here | |||
ReasoningLike-for-likePublic boards, shown as published, kept out of the index10
| Benchmark | Mercury 2.5 | 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) | 11.8% | 4.0% | Mercury 2.5 |
| Neither model has a result on the other 20 boards here | |||
MathDirectional onlyPublic boards, shown as published, kept out of the index1 board, none shared
| Benchmark | Mercury 2.5 | Mixtral 8x22B Instruct | Leader |
|---|---|---|---|
| ProofBench | 3.0% | Not measured | Only Mercury 2.5 measured |
| Neither model has a result on the other 12 boards here | |||
KnowledgeDirectional onlyPublic boards, shown as published, kept out of the index3 boards, none shared
| Benchmark | Mercury 2.5 | Mixtral 8x22B Instruct | Leader |
|---|---|---|---|
| LegalBench (Vals AI) | 83.1% | Not measured | Only Mercury 2.5 measured |
| MedCode (Vals AI) | 31.3% | Not measured | Only Mercury 2.5 measured |
| MMLU Pro (Artificial Analysis run) | Not measured | 53.7% | Only Mixtral 8x22B Instruct 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 | Mercury 2.5 | Mixtral 8x22B Instruct | Leader |
|---|---|---|---|
| Neither model has a result on 9 boards here | |||
GeneralDirectional onlyPublic boards, shown as published, kept out of the index4 boards, none shared
| Benchmark | Mercury 2.5 | Mixtral 8x22B Instruct | Leader |
|---|---|---|---|
| Public Benefits Bench (Vals AI) | 45.3% | Not measured | Only Mercury 2.5 measured |
| MedScribe (Vals AI) | 55.1% | Not measured | Only Mercury 2.5 measured |
| Long context reasoning (AA-LCR) | 71.7% | Not measured | Only Mercury 2.5 measured |
| DTBench | Not measured | 55.1% | Only Mixtral 8x22B Instruct measured |
| Neither model has a result on the other 42 boards here | |||
Image generationNot comparablePublic boards, shown as published, kept out of the index0 boards, none shared
| Benchmark | Mercury 2.5 | 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
Mercury 2.5 costs less
Repository review
50K input + 3K output tokens
Mercury 2.5 costs less
Agent loop
200K input + 10K output tokens
Mercury 2.5 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 | Inception Mercury 2.5 | Mistral Mixtral 8x22B Instruct |
|---|---|---|
| Maker | Inception | Mistral AI |
| Weights | No public weights listed | Open weights |
| Released | September 8, 2026 | April 17, 2024 |
| Context window | 260K | 66K |
| Input $/Mtok | $0.04 | $2.00 |
| Output $/Mtok | $0.15 | $6.00 |
| Coding index | 1.6 | Not benchmarked |
| Independent measurements behind it | 2 | 0 |
| Cost per solved task | Not computable | Not computable |
| Source | OpenRouter listing | OpenRouter listing |
Questions
Is Mercury 2.5 better than Mixtral 8x22B Instruct for coding?
Only Mercury 2.5 has a coding score, 1.6 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, Mercury 2.5 or Mixtral 8x22B Instruct?
Mercury 2.5 costs $0.04 per million input tokens and $0.15 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, Mercury 2.5 or Mixtral 8x22B Instruct?
Mercury 2.5, with 260K tokens against 66K.
How many benchmarks is the Mercury 2.5 vs Mixtral 8x22B Instruct comparison based on?
2 benchmarks have a result for both models as of October 21, 2026. Mercury 2.5'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.