Mercury 2 vs Mistral Small 3.2 24B
Mistral Small 3.2 24B costs 2.5x less per output token than Mercury 2 ($0.30 vs $0.75 per million). Updated October 22, 2026; 5 benchmarks have a result for both.
Mercury 2 or Mistral Small 3.2 24B: which to pick
Neither model has a coding score yet, so the two cannot be ranked on coding.
Compare them on price, context and the boards below.
- Shared results
- 5
- Mercury 2 only
- 37
- Mistral Small 3.2 24B only
- 0
- 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 Mercury 2 has a AA Intelligence Index result, 10.8.
Directional only
Agentic work
AA Agentic Index
No call
Only Mercury 2 has a AA Agentic Index result, 1.6.
Directional only
Web design
Design Arena: websites
Mercury 2
Mercury 2 leads, 1036 against 896.
Same board, both measured
Long documents
Listed context window
Mistral Small 3.2 24B
Mistral Small 3.2 24B takes 256K tokens against 128K.
Listed by OpenRouter
Everyday cost
1K input + 500 output tokens
Mistral Small 3.2 24B
Mercury 2 $0.0006, Mistral Small 3.2 24B $0.0003 per turn.
List prices
At a glance
- Coding index
- Mercury 2 not benchmarked, Mistral Small 3.2 24B not benchmarked.
- Widest category
- Web design, 12.9 points apart on average over 5 shared benchmarks.
- Widest single gap
- Design Arena: websites: Mercury 2 1036 against Mistral Small 3.2 24B 896, 17.5 points apart on a 0 to 100 scale.
- Output price
- Mercury 2 $0.75 against Mistral Small 3.2 24B $0.30 per million output tokens, 2.5x apart.
- Context window
- Mercury 2 takes 128K tokens, Mistral Small 3.2 24B 256K.
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 3.2 24B | Ties |
|---|---|---|---|---|
| Web design | 5 | 0 | ||
| All shared boards | 5 | 0 |
CodingDirectional onlySix of these boards feed the Vibe Coding Index10 boards, none shared
| Benchmark | Mercury 2 | Mistral Small 3.2 24B | Leader |
|---|---|---|---|
| LMArena WebDev | 1171 | Not measured | Only Mercury 2 measured |
| AA Coding Index | 31.1 | Not measured | Only Mercury 2 measured |
| SciCode | 37.7% | Not measured | Only Mercury 2 measured |
| Terminal-Bench Hard (Artificial Analysis run) | 26.5% | Not measured | Only Mercury 2 measured |
| WeirdML | 43.2% | Not measured | Only Mercury 2 measured |
| ALE-Bench | 785.6 | Not measured | Only Mercury 2 measured |
| 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 29 boards here | |||
IntelligenceDirectional onlyPublic boards, shown as published, kept out of the index1 board, none shared
| Benchmark | Mercury 2 | Mistral Small 3.2 24B | Leader |
|---|---|---|---|
| AA Intelligence Index | 10.8 | Not measured | Only Mercury 2 measured |
| Neither model has a result on the other 1 board here | |||
Agentic workDirectional onlyPublic boards, shown as published, kept out of the index2 boards, none shared
| Benchmark | Mercury 2 | Mistral Small 3.2 24B | Leader |
|---|---|---|---|
| AA Agentic Index | 1.6 | Not measured | Only Mercury 2 measured |
| τ²-Bench Telecom | 70.8% | Not measured | Only Mercury 2 measured |
| Neither model has a result on the other 39 boards here | |||
ReasoningDirectional onlyPublic boards, shown as published, kept out of the index5 boards, none shared
| Benchmark | Mercury 2 | Mistral Small 3.2 24B | Leader |
|---|---|---|---|
| GPQA Diamond (Artificial Analysis run) | 77.0% | Not measured | Only Mercury 2 measured |
| Humanity's Last Exam (Artificial Analysis run) | 17.1% | Not measured | Only Mercury 2 measured |
| 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 |
| Neither model has a result on the other 17 boards here | |||
MathNot comparablePublic boards, shown as published, kept out of the index0 boards, none shared
| Benchmark | Mercury 2 | Mistral Small 3.2 24B | 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 3.2 24B | 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 designLike-for-likePublic boards, shown as published, kept out of the index50
| Benchmark | Mercury 2 | Mistral Small 3.2 24B | Leader |
|---|---|---|---|
| Design Arena: websites | 1036 | 896 | Mercury 2 |
| Design Arena: UI components | 996 | 907 | Mercury 2 |
| Design Arena: game dev | 984 | 889 | Mercury 2 |
| Design Arena: data viz | 1009 | 929 | Mercury 2 |
| Design Arena: 3D | 982 | Not measured | Only Mercury 2 measured |
| Design Arena: all code categories | 1021 | 907 | Mercury 2 |
| 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 | |||
GeneralDirectional onlyPublic boards, shown as published, kept out of the index13 boards, none shared
| Benchmark | Mercury 2 | Mistral Small 3.2 24B | Leader |
|---|---|---|---|
| IFBench | 69.8% | Not measured | Only Mercury 2 measured |
| Long context reasoning (AA-LCR) | 43.7% | Not measured | Only Mercury 2 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 33 boards here | |||
Image generationNot comparablePublic boards, shown as published, kept out of the index0 boards, none shared
| Benchmark | Mercury 2 | Mistral Small 3.2 24B | 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 3.2 24B costs less
Repository review
50K input + 3K output tokens
Mistral Small 3.2 24B costs less
Agent loop
200K input + 10K output tokens
Mistral Small 3.2 24B 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 3.2 24B |
|---|---|---|
| Maker | Inception | Mistral AI |
| Weights | No public weights listed | Open weights |
| Released | March 4, 2026 | June 20, 2025 |
| Context window | 128K | 256K |
| Input $/Mtok | $0.25 | $0.10 |
| Output $/Mtok | $0.75 | $0.30 |
| 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 Mercury 2 better than Mistral Small 3.2 24B for coding?
Neither model has a coding score yet, so the two cannot be ranked on coding. Compare them on price, context and the boards below.
Which is cheaper, Mercury 2 or Mistral Small 3.2 24B?
Mercury 2 costs $0.25 per million input tokens and $0.75 per million output tokens; Mistral Small 3.2 24B costs $0.10 and $0.30. Cost per solved task is known for neither of them.
Which has the bigger context window, Mercury 2 or Mistral Small 3.2 24B?
Mistral Small 3.2 24B, with 256K tokens against 128K.
How many benchmarks is the Mercury 2 vs Mistral Small 3.2 24B comparison based on?
5 benchmarks have a result for both models as of October 22, 2026. Mercury 2's coding index rests on 1 independent benchmark and Mistral Small 3.2 24B's on 0. Where only one model has a result, the page says so instead of naming a winner.