Mercury 2 vs Mistral Small 4
Mistral Small 4 leads Mercury 2 on the Artificial Analysis Intelligence Index, 11.3 to 10.8, and Mistral Small 4 costs 1.3x less per output token ($0.60 vs $0.75 per million). Updated October 21, 2026; 11 benchmarks have a result for both.
Mercury 2 or Mistral Small 4: which to pick
Neither model has a coding score yet, so the two cannot be ranked on coding.
Pick Mercury 2 for work measured by SciCode or AA Intelligence Index, where it leads.
- Shared results
- 11
- Mercury 2 only
- 31
- Mistral Small 4 only
- 4
- Like-for-like categories
- 5 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
Mistral Small 4
Mistral Small 4 leads, 11.3 against 10.8.
Same board, both measured
Agentic work
AA Agentic Index
Mercury 2
Mercury 2 leads, 1.6 against 0.8.
Same board, both measured
Web design
Design Arena: websites
No call
Only Mercury 2 has a Design Arena: websites result, 1036.
Directional only
Long documents
Listed context window
Mistral Small 4
Mistral Small 4 takes 262K tokens against 128K.
Listed by OpenRouter
Everyday cost
1K input + 500 output tokens
Mistral Small 4
Mercury 2 $0.0006, Mistral Small 4 $0.0004 per turn.
List prices
At a glance
- Coding index
- Mercury 2 not benchmarked, Mistral Small 4 not benchmarked.
- Widest category
- Agentic work, 15.2 points apart on average over 2 shared benchmarks.
- Widest single gap
- τ²-Bench Telecom: Mercury 2 70.8% against Mistral Small 4 41.2%, 29.5 points apart on a 0 to 100 scale.
- Output price
- Mercury 2 $0.75 against Mistral Small 4 $0.60 per million output tokens, 1.3x apart.
- Context window
- Mercury 2 takes 128K tokens, Mistral Small 4 262K.
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 | Bars | Mistral Small 4 | Ties |
|---|---|---|---|---|
| Coding | 3 | 1 | ||
| Intelligence | 0 | 1 | ||
| Agentic work | 2 | 0 | ||
| Reasoning | 2 | 0 | ||
| General | 1 | 1 | ||
| All shared boards | 8 | 3 |
CodingLike-for-likeSix of these boards feed the Vibe Coding Index31
| Benchmark | Mercury 2 | Mistral Small 4 | Leader |
|---|---|---|---|
| LMArena WebDev | 1171 | Not measured | Only Mercury 2 measured |
| AA Coding Index | 31.1 | 26.6 | Mercury 2 |
| Vibe Code Bench (Vals AI) | Not measured | 0.0% | Only Mistral Small 4 measured |
| SciCode | 37.7% | 38.8% | Mistral Small 4 |
| Terminal-Bench Hard (Artificial Analysis run) | 26.5% | 17.4% | Mercury 2 |
| WeirdML | 43.2% | Not measured | Only Mercury 2 measured |
| ALE-Bench | 785.6 | 497.6 | Mercury 2 |
| LMArena Text: coding | 1390 | Not measured | Only Mercury 2 measured |
| LMArena Text: software and IT | 1385 | Not measured | Only Mercury 2 measured |
| LMArena WebDev: React | 1160 | Not measured | Only Mercury 2 measured |
| LMArena WebDev: HTML | 1199 | Not measured | Only Mercury 2 measured |
| Neither model has a result on the other 28 boards here | |||
IntelligenceLike-for-likePublic boards, shown as published, kept out of the index01
| Benchmark | Mercury 2 | Mistral Small 4 | Leader |
|---|---|---|---|
| AA Intelligence Index | 10.8 | 11.3 | Mistral Small 4 |
| Neither model has a result on the other 1 board here | |||
Agentic workLike-for-likePublic boards, shown as published, kept out of the index20
| Benchmark | Mercury 2 | Mistral Small 4 | Leader |
|---|---|---|---|
| AA Agentic Index | 1.6 | 0.8 | Mercury 2 |
| τ²-Bench Telecom | 70.8% | 41.2% | Mercury 2 |
| Neither model has a result on the other 39 boards here | |||
ReasoningLike-for-likePublic boards, shown as published, kept out of the index20
| Benchmark | Mercury 2 | Mistral Small 4 | Leader |
|---|---|---|---|
| GPQA Diamond (Artificial Analysis run) | 77.0% | 76.9% | Mercury 2 |
| Humanity's Last Exam (Artificial Analysis run) | 17.1% | 9.9% | Mercury 2 |
| LMArena Text: hard prompts | 1362 | Not measured | Only Mercury 2 measured |
| LMArena Text: expert | 1358 | Not measured | Only Mercury 2 measured |
| LMArena Text: hard prompts in English | 1374 | Not measured | Only Mercury 2 measured |
| Kagi LLM Benchmark | Not measured | 40.5% | Only Mistral Small 4 measured |
| Neither model has a result on the other 16 boards here | |||
MathNot comparablePublic boards, shown as published, kept out of the index0 boards, none shared
| Benchmark | Mercury 2 | Mistral Small 4 | Leader |
|---|---|---|---|
| Neither model has a result on 13 boards here | |||
KnowledgeDirectional onlyPublic boards, shown as published, kept out of the index3 boards, none shared
| Benchmark | Mercury 2 | Mistral Small 4 | Leader |
|---|---|---|---|
| LMArena Text: science | 1343 | Not measured | Only Mercury 2 measured |
| LMArena Text: medicine and healthcare | 1363 | Not measured | Only Mercury 2 measured |
| LMArena Text: business and finance | 1349 | Not measured | Only Mercury 2 measured |
| Neither model has a result on the other 15 boards here | |||
Web designDirectional onlyPublic boards, shown as published, kept out of the index8 boards, none shared
| Benchmark | Mercury 2 | Mistral Small 4 | Leader |
|---|---|---|---|
| Design Arena: websites | 1036 | Not measured | Only Mercury 2 measured |
| Design Arena: UI components | 998 | Not measured | Only Mercury 2 measured |
| Design Arena: game dev | 985 | Not measured | Only Mercury 2 measured |
| Design Arena: data viz | 1009 | Not measured | Only Mercury 2 measured |
| Design Arena: 3D | 983 | Not measured | Only Mercury 2 measured |
| Design Arena: all code categories | 1022 | Not measured | Only Mercury 2 measured |
| Design Arena: SVG | 998 | Not measured | Only Mercury 2 measured |
| Design Arena: ASCII art | 988 | Not measured | Only Mercury 2 measured |
| Neither model has a result on the other 1 board here | |||
GeneralLike-for-likePublic boards, shown as published, kept out of the index11
| Benchmark | Mercury 2 | Mistral Small 4 | Leader |
|---|---|---|---|
| IFBench | 69.8% | 48.2% | Mercury 2 |
| Long context reasoning (AA-LCR) | 43.7% | 49.7% | Mistral Small 4 |
| DTBench | Not measured | 70.9% | Only Mistral Small 4 measured |
| LMCA | Not measured | 20.6% | Only Mistral Small 4 measured |
| LMArena Text | 1354 | Not measured | Only Mercury 2 measured |
| LMArena Text: instruction following | 1328 | Not measured | Only Mercury 2 measured |
| LMArena Text: creative writing | 1286 | Not measured | Only Mercury 2 measured |
| LMArena Text: English | 1378 | Not measured | Only Mercury 2 measured |
| LMArena Text: non-English | 1330 | Not measured | Only Mercury 2 measured |
| LMArena Text: Chinese | 1414 | Not measured | Only Mercury 2 measured |
| LMArena Text: Russian | 1304 | Not measured | Only Mercury 2 measured |
| LMArena Text: multi-turn | 1357 | Not measured | Only Mercury 2 measured |
| LMArena Text: longer queries | 1329 | Not measured | Only Mercury 2 measured |
| LMArena Text: writing and language | 1300 | Not measured | Only Mercury 2 measured |
| LMArena Text: entertainment and media | 1314 | Not measured | Only Mercury 2 measured |
| Neither model has a result on the other 31 boards here | |||
Image generationNot comparablePublic boards, shown as published, kept out of the index0 boards, none shared
| Benchmark | Mercury 2 | Mistral Small 4 | 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
Mistral Small 4 costs less
Repository review
50K input + 3K output tokens
Mistral Small 4 costs less
Agent loop
200K input + 10K output tokens
Mistral Small 4 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 | Mistral Small 4 |
|---|---|---|
| Maker | Inception | Mistral AI |
| Weights | No public weights listed | Open weights |
| Released | March 4, 2026 | March 16, 2026 |
| Context window | 128K | 262K |
| Input $/Mtok | $0.25 | $0.15 |
| Output $/Mtok | $0.75 | $0.60 |
| Coding index | Not benchmarked | Not benchmarked |
| Independent measurements behind it | 1 | 1 |
| Cost per solved task | Not computable | Not computable |
| Source | OpenRouter listing | OpenRouter listing |
Questions
Is Mercury 2 better than Mistral Small 4 for coding?
Neither model has a coding score yet, so the two cannot be ranked on coding. Pick Mercury 2 for work measured by SciCode or AA Intelligence Index, where it leads.
Which is cheaper, Mercury 2 or Mistral Small 4?
Mercury 2 costs $0.25 per million input tokens and $0.75 per million output tokens; Mistral Small 4 costs $0.15 and $0.60. Cost per solved task is known for neither of them.
Which has the bigger context window, Mercury 2 or Mistral Small 4?
Mistral Small 4, with 262K tokens against 128K.
How many benchmarks is the Mercury 2 vs Mistral Small 4 comparison based on?
11 benchmarks have a result for both models as of October 21, 2026. Mercury 2's coding index rests on 1 independent benchmark and Mistral Small 4's on 1. Where only one model has a result, the page says so instead of naming a winner.