Model comparison
GLM-4.7 vs Kimi K2 (Jul 2025)
GLM-4.7 and Kimi K2 (Jul 2025) score almost the same on the Noometry Index (41.7 vs 40.9), so choose on price, context window or the category you care about most.
Last verified . 26 shared benchmarks.
Summary
- They share 26 benchmarks with published results for both. GLM-4.7 scores higher in 6 categories and Kimi K2 (Jul 2025) in 3 categories; 8 gaps are clear of the uncertainty.
- The widest gap is in knowledge, where GLM-4.7 leads 47.0 to 36.9.
- The biggest single-benchmark swing is SimpleBench: 47.7% for GLM-4.7 and 26.3% for Kimi K2 (Jul 2025).
- Both cost about the same: $0.60 input and $2.20 output per million tokens.
- Kimi K2 (Jul 2025) accepts more context: 262K tokens versus 205K.
Side by side
| GLM-4.7 | Kimi K2 (Jul 2025) | |
|---|---|---|
| Provider | Z.ai (Zhipu) | Moonshot AI |
| Noometry Index | 41.7 | 40.9 |
| Released | 2025-12-22 | 2025-07-12 |
| Weights | Open | Open |
| Context window | 205K | 262K |
| Max output | 131K | 262K |
| Input $ / M tokens | $0.60 | $0.57 |
| Output $ / M tokens | $2.20 | $2.30 |
| Results tracked | 36 | 42 |
Sponsored placements are available on pages like this one. Advertise on Noometry
Category by category
Coding Too close to call
GLM-4.7: 43.6 (#74), Kimi K2 (Jul 2025): 43.1 (#83)
| Benchmark | GLM-4.7 | Kimi K2 (Jul 2025) |
|---|---|---|
| LMArena Coding | 1454 | 1399 |
| ALE-Bench | 399.48 | 597.5 |
| SWE-bench Verified (bash only) | — | 63.4% |
| Aider Polyglot | — | 59.1% |
| LMArena WebDev | 1435 | — |
| SciCode | 45.1% | — |
| GSO | — | 4.9% |
| WeirdML | — | 42.8% |
Agentic & Tool Use Kimi K2 (Jul 2025) leads
GLM-4.7: 26.4 (#96), Kimi K2 (Jul 2025): 32.2 (#59)
| Benchmark | GLM-4.7 | Kimi K2 (Jul 2025) |
|---|---|---|
| Terminal-Bench | 33.4% | 35.7% |
| Berkeley Function Calling Leaderboard | — | 59.1% |
| METR Time Horizons | — | 59.2% |
| Vending-Bench 2 | 2,377 | — |
Reasoning GLM-4.7 leads
GLM-4.7: 23.7 (#161), Kimi K2 (Jul 2025): 22.7 (#173)
| Benchmark | GLM-4.7 | Kimi K2 (Jul 2025) |
|---|---|---|
| SimpleBench | 47.7% | 26.3% |
| LMArena Hard Prompts | 1443 | 1384 |
| Epoch Capabilities Index | 143.53 | 146.02 |
| Kagi LLM Benchmark | — | 64.4% |
| CritPt | 1.7% | — |
| Chess Puzzles | 6% | — |
| ForecastBench | — | 60.2 |
Math Kimi K2 (Jul 2025) leads
GLM-4.7: 37.7 (#92), Kimi K2 (Jul 2025): 40.1 (#81)
| Benchmark | GLM-4.7 | Kimi K2 (Jul 2025) |
|---|---|---|
| LMArena Math | 1423 | 1396 |
| FrontierMath (Feb 2025 set) | 2.4% | 21.4% |
| FrontierMath Tier 4 (v1) | 0% | 0% |
| OTIS Mock AIME 2024-2025 | 83.3% | — |
| ProofBench | 6% | — |
| Omni-MATH | — | 65.4% |
Knowledge GLM-4.7 leads
GLM-4.7: 47.0 (#74), Kimi K2 (Jul 2025): 36.9 (#153)
| Benchmark | GLM-4.7 | Kimi K2 (Jul 2025) |
|---|---|---|
| Vectara Hallucination Rate | 11.7% | 17.9% |
| LMArena Expert | 1424 | 1363 |
| GPQA Diamond | 83.3% | — |
| SimpleQA Verified | 32.2% | — |
| MMLU-Pro | — | 81.9% |
| Confabulations | — | 20.4% |
| GPQA (HELM) | — | 65.3% |
Multilingual GLM-4.7 leads
GLM-4.7: 53.0 (#75), Kimi K2 (Jul 2025): 49.8 (#125)
| Benchmark | GLM-4.7 | Kimi K2 (Jul 2025) |
|---|---|---|
| LMArena Non-English | 1417 | 1372 |
| LMArena Chinese | 1495 | 1416 |
| LMArena French | 1432 | 1379 |
| LMArena German | 1426 | 1386 |
| LMArena Japanese | 1439 | 1349 |
| LMArena Korean | 1401 | 1324 |
| LMArena Russian | 1423 | 1384 |
| LMArena Spanish | 1433 | 1383 |
Instruction Following GLM-4.7 leads
GLM-4.7: 74.6 (#90), Kimi K2 (Jul 2025): 71.3 (#151)
| Benchmark | GLM-4.7 | Kimi K2 (Jul 2025) |
|---|---|---|
| LMArena Instruction Following | 1411 | 1347 |
| IFEval | — | 85% |
Long Context GLM-4.7 leads
GLM-4.7: 42.8 (#111), Kimi K2 (Jul 2025): 41.2 (#140)
| Benchmark | GLM-4.7 | Kimi K2 (Jul 2025) |
|---|---|---|
| CL-bench | 15.9% | 17.6% |
| LMArena Longer Query | 1432 | 1353 |
| Fiction.LiveBench | — | 66.7% |
| CL-bench Life | 10.9% | — |
Writing & Preference Kimi K2 (Jul 2025) leads
GLM-4.7: 61.1 (#89), Kimi K2 (Jul 2025): 62.5 (#76)
| Benchmark | GLM-4.7 | Kimi K2 (Jul 2025) |
|---|---|---|
| LMArena Text | 1436 | 1380 |
| LMArena Creative Writing | 1401 | 1349 |
| EQ-Bench Creative Writing | 1413 | 1666 |
| LMArena Multi-Turn | 1446 | 1371 |
| Short-Story Creative Writing | — | 85.6% |
| WildBench | — | 86.2% |
Frequently asked questions
Is GLM-4.7 better than Kimi K2 (Jul 2025)?
GLM-4.7 and Kimi K2 (Jul 2025) score almost the same on the Noometry Index (41.7 vs 40.9), so choose on price, context window or the category you care about most.
Which is cheaper, GLM-4.7 or Kimi K2 (Jul 2025)?
GLM-4.7 is cheaper. It lists at $0.60 per million input tokens and $2.20 per million output tokens; Kimi K2 (Jul 2025) lists at $0.57 and $2.30.
Is GLM-4.7 or Kimi K2 (Jul 2025) better for coding?
They score almost the same on coding (43.6 vs 43.1); test both on your own repository before choosing.
Which has the bigger context window?
Kimi K2 (Jul 2025) does, with 262K tokens against 205K.
How many benchmarks do GLM-4.7 and Kimi K2 (Jul 2025) share?
26 benchmarks have published results for both models. GLM-4.7 has 36 scored results on Noometry and Kimi K2 (Jul 2025) has 42.