Mercury 2.5 vs Kimi K3.1 Pro
Kimi K3.1 Pro leads Mercury 2.5 on coding, 82.2 to 1.6 on the Vibe Coding Index, and Mercury 2.5 costs 66.7x less per output token ($0.15 vs $10.00 per million). Updated October 29, 2026; 11 benchmarks have a result for both.
Mercury 2.5 or Kimi K3.1 Pro: which to pick
Pick Kimi K3.1 Pro for coding: it scores 82.2 on the Vibe Coding Index against 1.6 for Mercury 2.5.
Pick Mercury 2.5 for output tokens 66.7x cheaper ($0.15 vs $10.00 per million).
- Shared results
- 11
- Mercury 2.5 only
- 10
- Kimi K3.1 Pro only
- 24
- 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
Kimi K3.1 Pro
Kimi K3.1 Pro scores 82.2 against 1.6.
2 and 4 benchmarks behind the scores
Intelligence
AA Intelligence Index
No call
Only Kimi K3.1 Pro has a AA Intelligence Index result, 46.0.
Directional only
Web design
Design Arena: websites
No call
Only Kimi K3.1 Pro has a Design Arena: websites result, 1325.
Directional only
General
Vals Index
No call
Only Kimi K3.1 Pro has a Vals Index result, 62.5%.
Directional only
Long documents
Listed context window
Kimi K3.1 Pro
Kimi K3.1 Pro takes 1.05M tokens against 260K.
Listed by OpenRouter
Everyday cost
1K input + 500 output tokens
Mercury 2.5
Mercury 2.5 $0.0001, Kimi K3.1 Pro $0.0070 per turn.
List prices
At a glance
- Coding index
- Mercury 2.5 1.6 from 2 benchmarks, Kimi K3.1 Pro 82.2 from 4 benchmarks.
- Widest category
- Math, 88.0 points apart on average over 1 shared benchmark.
- Widest single gap
- ProofBench: Mercury 2.5 3.0% against Kimi K3.1 Pro 91.0%, 88.0 points apart on a 0 to 100 scale.
- Output price
- Mercury 2.5 $0.15 against Kimi K3.1 Pro $10.00 per million output tokens, 66.7x apart.
- Context window
- Mercury 2.5 takes 260K tokens, Kimi K3.1 Pro 1.05M.
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 | Kimi K3.1 Pro | Ties |
|---|---|---|---|---|
| Coding | 0 | 5 | ||
| Agentic work | 0 | 3 | ||
| Reasoning | 0 | 1 | ||
| Math | 0 | 1 | ||
| General | 0 | 1 | ||
| All shared boards | 0 | 11 |
CodingLike-for-likeSix of these boards feed the Vibe Coding Index05
| Benchmark | Mercury 2.5 | Kimi K3.1 Pro | Leader |
|---|---|---|---|
| LiveBench coding | Not measured | 81.8% | Only Kimi K3.1 Pro measured |
| LMArena WebDev | Not measured | 1695 | Only Kimi K3.1 Pro measured |
| Terminal-Bench 4 (Vals AI) | 0.0% | 63.6% | Kimi K3.1 Pro |
| Vibe Code Bench (Vals AI) | 3.7% | 84.9% | Kimi K3.1 Pro |
| Code migration (Vals AI) | 4.5% | Not measured | Only Mercury 2.5 measured |
| IOI (Vals AI) | 2.4% | 81.9% | Kimi K3.1 Pro |
| 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 |
| SciCode | 38.5% | 60.8% | Kimi K3.1 Pro |
| ALE-Bench | 301.6 | 1932.8 | Kimi K3.1 Pro |
| LMArena WebDev: React | Not measured | 1701 | Only Kimi K3.1 Pro measured |
| LMArena WebDev: HTML | Not measured | 1706 | Only Kimi K3.1 Pro measured |
| Neither model has a result on the other 30 boards here | |||
IntelligenceDirectional onlyPublic boards, shown as published, kept out of the index1 board, none shared
| Benchmark | Mercury 2.5 | Kimi K3.1 Pro | Leader |
|---|---|---|---|
| AA Intelligence Index | Not measured | 46.0 | Only Kimi K3.1 Pro measured |
| Neither model has a result on the other 1 board here | |||
Agentic workLike-for-likePublic boards, shown as published, kept out of the index03
| Benchmark | Mercury 2.5 | Kimi K3.1 Pro | Leader |
|---|---|---|---|
| LiveBench research | Not measured | 77.9% | Only Kimi K3.1 Pro measured |
| LiveBench browser | Not measured | 75.9% | Only Kimi K3.1 Pro measured |
| LiveBench long agentic | Not measured | 39.1% | Only Kimi K3.1 Pro measured |
| Finance Agent (Vals AI) | 18.9% | Not measured | Only Mercury 2.5 measured |
| Tax Agent Bench (Vals AI) | 2.5% | 24.9% | Kimi K3.1 Pro |
| Legal Research Bench (Vals AI) | 4.3% | 37.5% | Kimi K3.1 Pro |
| Harvey's Legal Agent Benchmark (Vals AI) | Not measured | 11.7% | Only Kimi K3.1 Pro measured |
| Excel Modeling Benchmark (Vals AI) | 8.8% | Not measured | Only Mercury 2.5 measured |
| BioMysteryBench (Vals AI) | Not measured | 75.6% | Only Kimi K3.1 Pro measured |
| Terminal-Bench-Science (Vals AI) | 0.0% | 31.4% | Kimi K3.1 Pro |
| Vals Science Index | Not measured | 44.4% | Only Kimi K3.1 Pro measured |
| Neither model has a result on the other 31 boards here | |||
ReasoningLike-for-likePublic boards, shown as published, kept out of the index01
| Benchmark | Mercury 2.5 | Kimi K3.1 Pro | Leader |
|---|---|---|---|
| LiveBench reasoning | Not measured | 91.1% | Only Kimi K3.1 Pro measured |
| MysteryMechanism (Vals AI) | Not measured | 26.1% | Only Kimi K3.1 Pro measured |
| Humanity's Last Exam (Artificial Analysis run) | 11.8% | 52.5% | Kimi K3.1 Pro |
| Neither model has a result on the other 20 boards here | |||
MathLike-for-likePublic boards, shown as published, kept out of the index01
| Benchmark | Mercury 2.5 | Kimi K3.1 Pro | Leader |
|---|---|---|---|
| ProofBench | 3.0% | 91.0% | Kimi K3.1 Pro |
| MathArena | Not measured | 59.6% | Only Kimi K3.1 Pro measured |
| Neither model has a result on the other 12 boards here | |||
KnowledgeDirectional onlyPublic boards, shown as published, kept out of the index2 boards, none shared
| Benchmark | Mercury 2.5 | Kimi K3.1 Pro | 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 |
| Neither model has a result on the other 18 boards here | |||
Web designDirectional onlyPublic boards, shown as published, kept out of the index8 boards, none shared
| Benchmark | Mercury 2.5 | Kimi K3.1 Pro | Leader |
|---|---|---|---|
| Design Arena: websites | Not measured | 1325 | Only Kimi K3.1 Pro measured |
| Design Arena: UI components | Not measured | 1400 | Only Kimi K3.1 Pro measured |
| Design Arena: game dev | Not measured | 1410 | Only Kimi K3.1 Pro measured |
| Design Arena: data viz | Not measured | 1300 | Only Kimi K3.1 Pro measured |
| Design Arena: 3D | Not measured | 1451 | Only Kimi K3.1 Pro measured |
| Design Arena: all code categories | Not measured | 1354 | Only Kimi K3.1 Pro measured |
| Design Arena: SVG | Not measured | 1328 | Only Kimi K3.1 Pro measured |
| LiveBench design | Not measured | 77.8% | Only Kimi K3.1 Pro measured |
| Neither model has a result on the other 1 board here | |||
GeneralLike-for-likePublic boards, shown as published, kept out of the index01
| Benchmark | Mercury 2.5 | Kimi K3.1 Pro | Leader |
|---|---|---|---|
| Vals Index | Not measured | 62.5% | Only Kimi K3.1 Pro measured |
| LiveBench data analysis | Not measured | 79.1% | Only Kimi K3.1 Pro measured |
| 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% | 86.3% | Kimi K3.1 Pro |
| Neither model has a result on the other 43 boards here | |||
Image generationNot comparablePublic boards, shown as published, kept out of the index0 boards, none shared
| Benchmark | Mercury 2.5 | Kimi K3.1 Pro | 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 | MoonshotAI Kimi K3.1 Pro |
|---|---|---|
| Maker | Inception | Moonshot AI |
| Weights | No public weights listed | No public weights listed |
| Released | September 8, 2026 | October 23, 2026 |
| Context window | 260K | 1.05M |
| Input $/Mtok | $0.04 | $2.00 |
| Output $/Mtok | $0.15 | $10.00 |
| Coding index | 1.6 | 82.2 |
| Independent measurements behind it | 2 | 4 |
| Cost per solved task | Not computable | Not computable |
| Source | OpenRouter listing | OpenRouter listing |
Questions
Is Mercury 2.5 better than Kimi K3.1 Pro for coding?
Pick Kimi K3.1 Pro for coding: it scores 82.2 on the Vibe Coding Index against 1.6 for Mercury 2.5. Pick Mercury 2.5 for output tokens 66.7x cheaper ($0.15 vs $10.00 per million).
Which is cheaper, Mercury 2.5 or Kimi K3.1 Pro?
Mercury 2.5 costs $0.04 per million input tokens and $0.15 per million output tokens; Kimi K3.1 Pro costs $2.00 and $10.00. Cost per solved task is known for neither of them.
Which has the bigger context window, Mercury 2.5 or Kimi K3.1 Pro?
Kimi K3.1 Pro, with 1.05M tokens against 260K.
How many benchmarks is the Mercury 2.5 vs Kimi K3.1 Pro comparison based on?
11 benchmarks have a result for both models as of October 29, 2026. Mercury 2.5's coding index rests on 2 independent benchmarks and Kimi K3.1 Pro's on 4. Where only one model has a result, the page says so instead of naming a winner.