Model comparison
GLM-5-Turbo vs Kimi K2.6
Head-to-head evidence from 14 shared benchmark results across 6 categories. Overall scores shown here use BenchLM's provisional ranking lane.
Verified leaderboard positions: GLM-5-Turbo unranked; Kimi K2.6 #13
Evidence parity. GLM-5-Turbo and Kimi K2.6 share 14 comparable benchmark results. 0 of 8 categories are comparable. 0 results are unique to GLM-5-Turbo; 46 to Kimi K2.6.
Updated July 13, 2026- Shared results
- 14
- GLM-5-Turbo only
- 0
- Kimi K2.6 only
- 46
- Comparable categories
- 0 / 8
Benchmark data for GLM-5-Turbo and Kimi K2.6 is coming soon on BenchLM.
Confidence note. This is a partial-evidence comparison with 14 shared benchmark results across 6 evidence categories; 0 of 8 categories currently have scoreable aggregates for both models. Treat the verdict as directional until coverage is more balanced.
Why this result
BenchLM has partial data for these models, but not enough overlapping benchmark coverage to produce a fair score-level comparison yet.
Kimi K2.6 has the larger context window at 256K, compared with 200K for GLM-5-Turbo.
Category breakdown
Exact category averages are shown below. Not measured means BenchLM does not have enough sourced public coverage for that model and category.
| Category | GLM-5-Turbo | Δ | Kimi K2.6 |
|---|---|---|---|
| Agentic | GLM-5-TurboNot measured | MarginNo overlap | Kimi K2.673.5 |
| Coding | GLM-5-TurboNot measured | MarginNo overlap | Kimi K2.672.6 |
| Knowledge | GLM-5-TurboNot measured | MarginNo overlap | Kimi K2.642.2 |
| Math | GLM-5-TurboNot measured | MarginNo overlap | Kimi K2.667.1 |
| Multimodal | GLM-5-TurboNot measured | MarginNo overlap | Kimi K2.679.8 |
Operational comparison
Runtime and commercial metrics are compared only when both models have a complete sourced value.
| Metric | GLM-5-Turbo | Kimi K2.6 | Comparison |
|---|---|---|---|
| Input / output priceUSD per 1M tokens | GLM-5-Turbo$1.2 input / $4 output | Kimi K2.6$0.95 input / $4 output | Kimi K2.6 has the lower combined listed price. |
| Generation speedtokens per second | GLM-5-TurboNot available | Kimi K2.6Not available | A complete speed comparison is not available. |
| First-answer latencyseconds to first token | GLM-5-TurboNot available | Kimi K2.6Not available | A complete latency comparison is not available. |
| Context windowmaximum listed tokens | GLM-5-Turbo200K | Kimi K2.6256K | Kimi K2.6 lists the larger context window. |
Benchmark Deep Dive
Agentic22 benchmarks
| Benchmark | GLM-5-Turbo | Kimi K2.6 | Result |
|---|---|---|---|
| Claw-EvalSource | 55.8% | 62.3% | Kimi K2.6 leads |
| Tau2-TelecomSource | 98.5% | 95.9% | GLM-5-Turbo leads |
| Terminal-Bench 2.0Source | — | 66.7% | Not comparable |
| BrowseCompSource | — | 83.2% | Not comparable |
| OSWorld-VerifiedSource | — | 73.1% | Not comparable |
| ToolathlonSource | — | 50% | Not comparable |
| MCP AtlasSource | — | 55.9% | Not comparable |
| DeepSearchQASource | — | 92.5% | Not comparable |
| WideResearchSource | — | 80.8% | Not comparable |
| AA Agentic IndexSource | — | 30.3% | Not comparable |
| GDPval-AASource | — | 34.5% | Not comparable |
| GDPval-AASource | — | 1190 | Not comparable |
| APEX-Agents-AASource | — | 28.5% | Not comparable |
| Gert LabsSource | — | 56.82% | Not comparable |
| ResearchClawBenchSource | — | 18.0% | Not comparable |
| OSWorld 2.0Source | — | 4.6% | Not comparable |
| AA BriefcaseSource | — | 809 | Not comparable |
| AA AutomationBenchSource | — | 19.6% | Not comparable |
| AA EnterpriseOps-GymSource | — | 38.5% | Not comparable |
| AA Harvey LABSource | — | 0.0% | Not comparable |
| AA ITBenchSource | — | 31.2% | Not comparable |
| AA Tau3 BankingSource | — | 20.6% | Not comparable |
Coding13 benchmarks
| Benchmark | GLM-5-Turbo | Kimi K2.6 | Result |
|---|---|---|---|
| Terminal-Bench HardSource | 33.3% | 43.9% | Kimi K2.6 leads |
| AA-SciCodeSource | 43.6% | 53.5% | Kimi K2.6 leads |
| SWE-bench VerifiedSource | — | 80.2% | Not comparable |
| LiveCodeBenchSource | — | 89.6% | Not comparable |
| LiveCodeBench v6Source | — | 89.6% | Not comparable |
| SWE-bench ProSource | — | 58.6% | Not comparable |
| SWE MultilingualSource | — | 76.7% | Not comparable |
| SciCodeSource | — | 52.2% | Not comparable |
| Terminal-Bench 2.0Source | — | 66.7% | Not comparable |
| Vibe Code BenchSource | — | 37.89% | Not comparable |
| cursorBench31Source | — | 47.6% | Not comparable |
| AA Coding IndexSource | — | 61.8% | Not comparable |
| AA Terminal-Bench 2.1Source | — | 65.9% | Not comparable |
Reasoning2 benchmarks
Knowledge10 benchmarks
| Benchmark | GLM-5-Turbo | Kimi K2.6 | Result |
|---|---|---|---|
| Artificial Analysis Intelligence IndexSource | 38.1% | 44.2% | Kimi K2.6 leads |
| AA-GPQA DiamondSource | 84.7% | 91.1% | Kimi K2.6 leads |
| AA-HLESource | 25.4% | 35.9% | Kimi K2.6 leads |
| AA-Omniscience IndexSource | -15.1% | 6.4% | Kimi K2.6 leads |
| AA-Omniscience AccuracySource | 29.0% | 32.8% | Kimi K2.6 leads |
| AA-Omniscience Hallucination RateSource | 62.2% | 39.3% | Kimi K2.6 leads |
| GPQASource | — | 90.5% | Not comparable |
| GPQA-DSource | — | 90.5% | Not comparable |
| HLESource | — | 34.7% | Not comparable |
| AA Openness IndexSource | — | 33.3% | Not comparable |
Math5 benchmarks
Multimodal7 benchmarks
| Benchmark | GLM-5-Turbo | Kimi K2.6 | Result |
|---|---|---|---|
| Design Arena WebsiteSource | 1315 | 1318 | Kimi K2.6 leads |
| MMMU-ProSource | — | 79.4% | Not comparable |
| MMMU-Pro w/ PythonSource | — | 80.1% | Not comparable |
| CharXivSource | — | 80.4% | Not comparable |
| MathVisionSource | — | 87.4% | Not comparable |
| V*Source | — | 96.9% | Not comparable |
| AA-MMMU-ProSource | — | 79.4% | Not comparable |
Inst. Following1 benchmarks
| Benchmark | GLM-5-Turbo | Kimi K2.6 | Result |
|---|---|---|---|
| AA-IFBenchSource | 73.2% | 76.0% | Kimi K2.6 leads |
Frequently Asked Questions (3)
Can I compare GLM-5-Turbo and Kimi K2.6 on BenchLM yet?
Not fully yet. BenchLM is tracking both models, but the sourced benchmark breakdown for this comparison is still coming soon.
Why does this comparison show “coming soon”?
BenchLM only shows category winners and benchmark-level calls when we have sourced results that can be compared fairly. For these models, the public benchmark coverage is not complete enough yet.
What data is available for GLM-5-Turbo and Kimi K2.6 today?
GLM-5-Turbo: $1.20 input / $4.00 output per 1M tokens Kimi K2.6: $0.95 input / $4.00 output per 1M tokens Both model pages still include creator, context window, reasoning mode, and other metadata while benchmark coverage fills in.
Self-host vs API cost
Estimates at 50,000 req/day · 1000 tokens/req average.
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