Model comparison
Kimi K2 (Jul 2025) vs Mercury 2.5
Kimi K2 (Jul 2025) is the stronger model overall, scoring 41.2 to 33.5 on the Noometry Index. Mercury 2.5 costs 15× less per token, which makes it the better buy when Kimi K2 (Jul 2025)'s lead doesn't matter for your workload.
Last verified . 1 shared benchmarks.
Summary
- They share 1 benchmark with published results for both. Kimi K2 (Jul 2025) scores higher in 3 categories and Mercury 2.5 in 0 categories; 2 gaps are clear of the uncertainty.
- The widest gap is in math, where Kimi K2 (Jul 2025) leads 42.7 to 23.3.
- Mercury 2.5 is cheaper at $0.04 / $0.15 per million input/output tokens, against $0.57 / $2.30 for Kimi K2 (Jul 2025).
- Kimi K2 (Jul 2025) accepts more context: 262K tokens versus 260K.
- Kimi K2 (Jul 2025) has downloadable open weights; the other is API-only.
Side by side
| Kimi K2 (Jul 2025) | Mercury 2.5 | |
|---|---|---|
| Provider | Moonshot AI | Inception |
| Noometry Index | 41.2 | 33.5 |
| Released | 2025-07-12 | 2026-09-08 |
| Weights | Open | Proprietary |
| Context window | 262K | 260K |
| Max output | 262K | 66K |
| Input $ / M tokens | $0.57 | $0.04 |
| Output $ / M tokens | $2.30 | $0.15 |
| Results tracked | 42 | 4 |
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Category by category
Coding Kimi K2 (Jul 2025) leads
Kimi K2 (Jul 2025): 42.4 (#102), Mercury 2.5: 39.5 (#156)
| Benchmark | Kimi K2 (Jul 2025) | Mercury 2.5 |
|---|---|---|
| ALE-Bench | 597.5 | 301.65 |
| SWE-bench Verified (bash only) | 63.4% | — |
| Aider Polyglot | 59.1% | — |
| SciCode | — | 38.5% |
| GSO | 4.9% | — |
| WeirdML | 42.8% | — |
| LMArena Coding | 1399 | — |
Agentic & Tool Use Not comparable
Kimi K2 (Jul 2025): 32.4 (#64), Mercury 2.5: —
| Benchmark | Kimi K2 (Jul 2025) | Mercury 2.5 |
|---|---|---|
| Terminal-Bench | 35.7% | — |
| Berkeley Function Calling Leaderboard | 59.1% | — |
| METR Time Horizons | 59.2% | — |
Reasoning Too close to call
Kimi K2 (Jul 2025): 23.3 (#179), Mercury 2.5: 22.4 (#193)
| Benchmark | Kimi K2 (Jul 2025) | Mercury 2.5 |
|---|---|---|
| SimpleBench | 26.3% | — |
| Kagi LLM Benchmark | 64.4% | — |
| CritPt | — | 0% |
| LMArena Hard Prompts | 1384 | — |
| Epoch Capabilities Index | 146.01 | — |
| ForecastBench | 60.2 | — |
Math Kimi K2 (Jul 2025) leads
Kimi K2 (Jul 2025): 42.7 (#83), Mercury 2.5: 23.3 (#272)
| Benchmark | Kimi K2 (Jul 2025) | Mercury 2.5 |
|---|---|---|
| ProofBench | — | 3% |
| Omni-MATH | 65.4% | — |
| LMArena Math | 1397 | — |
| FrontierMath (Feb 2025 set) | 21.4% | — |
| FrontierMath Tier 4 (v1) | 0% | — |
Knowledge Not comparable
Kimi K2 (Jul 2025): 37.3 (#157), Mercury 2.5: —
| Benchmark | Kimi K2 (Jul 2025) | Mercury 2.5 |
|---|---|---|
| MMLU-Pro | 81.9% | — |
| Confabulations | 20.4% | — |
| Vectara Hallucination Rate | 17.9% | — |
| GPQA (HELM) | 65.3% | — |
| LMArena Expert | 1365 | — |
Multilingual Not comparable
Kimi K2 (Jul 2025): 49.6 (#130), Mercury 2.5: —
| Benchmark | Kimi K2 (Jul 2025) | Mercury 2.5 |
|---|---|---|
| LMArena Non-English | 1372 | — |
| LMArena Chinese | 1415 | — |
| LMArena French | 1379 | — |
| LMArena German | 1387 | — |
| LMArena Japanese | 1349 | — |
| LMArena Korean | 1325 | — |
| LMArena Russian | 1385 | — |
| LMArena Spanish | 1386 | — |
Instruction Following Not comparable
Kimi K2 (Jul 2025): 71.1 (#156), Mercury 2.5: —
| Benchmark | Kimi K2 (Jul 2025) | Mercury 2.5 |
|---|---|---|
| IFEval | 85% | — |
| LMArena Instruction Following | 1348 | — |
Long Context Not comparable
Kimi K2 (Jul 2025): 41.2 (#145), Mercury 2.5: —
| Benchmark | Kimi K2 (Jul 2025) | Mercury 2.5 |
|---|---|---|
| Fiction.LiveBench | 66.7% | — |
| CL-bench | 17.6% | — |
| LMArena Longer Query | 1353 | — |
Writing & Preference Not comparable
Kimi K2 (Jul 2025): 62.3 (#78), Mercury 2.5: —
| Benchmark | Kimi K2 (Jul 2025) | Mercury 2.5 |
|---|---|---|
| LMArena Text | 1380 | — |
| LMArena Creative Writing | 1350 | — |
| Short-Story Creative Writing | 85.6% | — |
| EQ-Bench Creative Writing | 1666 | — |
| WildBench | 86.2% | — |
| LMArena Multi-Turn | 1371 | — |
Frequently asked questions
Is Kimi K2 (Jul 2025) better than Mercury 2.5?
Kimi K2 (Jul 2025) is the stronger model overall, scoring 41.2 to 33.5 on the Noometry Index. Mercury 2.5 costs 15× less per token, which makes it the better buy when Kimi K2 (Jul 2025)'s lead doesn't matter for your workload.
Which is cheaper, Kimi K2 (Jul 2025) or Mercury 2.5?
Mercury 2.5 is cheaper. It lists at $0.04 per million input tokens and $0.15 per million output tokens; Kimi K2 (Jul 2025) lists at $0.57 and $2.30.
Is Kimi K2 (Jul 2025) or Mercury 2.5 better for coding?
Kimi K2 (Jul 2025) scores higher on coding benchmarks: 42.4 versus 39.5 in the Noometry coding category.
Which has the bigger context window?
Kimi K2 (Jul 2025) does, with 262K tokens against 260K.
How many benchmarks do Kimi K2 (Jul 2025) and Mercury 2.5 share?
1 benchmark has published results for both models. Kimi K2 (Jul 2025) has 42 scored results on Noometry and Mercury 2.5 has 4.