Kimi K2.7 Code vs GLM 5.2
At a Glance
| Compare |  Kimi K2.7 CodeMoonshot AI |  GLM 5.2Z.ai |
|---|---|---|
| Intelligence, Cost, and Efficiency | ||
| IntelligenceHigher is better · MM Intelligence v2.5 | UnrankedNot in the 46-model eligible cohort | #23 of 4661.9 score · 2/3 sources · provisional · missing ARC-AGI-2 · full-core range 41.3–74.6 |
| CostLower is better · Published-token output estimate | #9 of 44$0.042 per LiveBench case | #12 of 44$0.056 per LiveBench case |
| EfficiencyHigher is better · MM Efficiency v1.5 | UnrankedNot in the 38-model eligible cohort | #7 of 3861.3 score · 2/3 sources · provisional · missing ARC-AGI-2 · full-core range 51.0–67.6 |
| Pricing and Limits | ||
| Input priceFrom · USD / 1M tokens | $0.68Deepinfra ↗ · Sep 22, 2026 | $0.75Deepinfra ↗ · Sep 22, 2026 |
| Output priceFrom · USD / 1M tokens | $3.21Openrouter ↗ · Sep 22, 2026 | $2.40Deepinfra ↗ · Sep 22, 2026 |
| Context windowMaximum documented tokens | 262K | 1,049K |
| Model facts checked | Sep 3, 2026View model evidence → | Aug 28, 2026View model evidence → |
Token prices are the lowest available sourced USD rates; input and output may use different providers. Cost ranking estimates output spend on LiveBench, not a full request bill. Ranking methodology →
Available Benchmarks
| Benchmark | Kimi K2.7 Code | GLM-5.2 |
|---|---|---|
| LiveBench2026-06-25 · overall · leader | 71.4593% of row best · percent · kimi-k2.7-code · 13,007 output tokens / case | 76.96100% of row best · percent · glm-5.2 · 23,463 output tokens / case |
| Overall ResultCounted from the protocol-matched rows above | 0 benchmark winsNo overall winner | 1 benchmark winNo overall winner |
Third-party benchmark Only like-for-like primary-publisher results are shown; raw scores, relative scores, configuration, and token spend remain visible.
Side-by-Side Facts
| Field | Kimi K2.7 Code | GLM-5.2 |
|---|---|---|
| Developer | Moonshot AI | Z.ai |
| Family | Kimi K2 7 | Glm 5 2 |
| Model | Kimi K2.7 Code | GLM-5.2 |
| Version | Kimi K2.7 Code | GLM-5.2 |
| Lifecycle | active | active |
| Released | 2026-06-11 | Unknown |
| Knowledge cutoff | Unknown | Unknown |
| Input modalities | Text, Image, Video | Text |
| Output modalities | Text | Text |
| Context window | 262K | 1,049K |
| Total parameters | 1T | 753.3B |
| Active parameters | 32B | Unknown |
| License | modified-mit | mit |
| Open weights | Yes | Yes |
| API available | Yes | Yes |
| Self-hostable | Yes | Yes |
| Provider access | Deepinfra (Standard), Fireworks Ai (Standard), Openrouter (Standard), Together Ai (Standard) | Deepinfra (Standard), Fireworks Ai (Standard), Hugging Face (Standard), Openrouter (Standard), Together Ai (Standard) |
| Capabilities | agents, chat, coding, reasoning, tools, vision | chat, generation, reasoning, tools |
Kimi K2.7 Code Capabilities
GLM 5.2 Capabilities
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Primary Evidence
Sources and Freshness
Questions
Kimi K2.7 Code vs GLM 5.2 FAQs
Is Kimi K2.7 Code or GLM 5.2 better for coding?+
This comparison does not currently contain a protocol-matched coding benchmark for both Kimi K2.7 Code and GLM 5.2, so Model Markets cannot name a coding leader from pricing, context size, or capability labels alone.
Which is cheaper, Kimi K2.7 Code or GLM 5.2?+
Kimi K2.7 Code is $0.68 and GLM 5.2 is $0.75 per million tokens, so Kimi K2.7 Code is cheaper on this metric. Kimi K2.7 Code is $3.21 and GLM 5.2 is $2.40 per million tokens, so GLM 5.2 is cheaper on this metric.
Which has a larger context window, Kimi K2.7 Code or GLM 5.2?+
GLM 5.2 has the larger sourced context window. Kimi K2.7 Code supports 262K and GLM 5.2 supports 1,049K.
Which performs better in benchmarks, Kimi K2.7 Code or GLM 5.2?+
There is no overall benchmark winner: At least two independently verified, protocol-matched benchmarks are required for an overall winner.
Can Kimi K2.7 Code or GLM 5.2 be self-hosted?+
Both models have the same recorded self-hosting status: supported. Kimi K2.7 Code is open weight; GLM 5.2 is open weight.
Can Kimi K2.7 Code and GLM 5.2 understand images?+
Kimi K2.7 Code is documented with image input; GLM 5.2 is not documented with image input. This reflects supported input modalities, not vision quality.
Which can generate longer answers, Kimi K2.7 Code or GLM 5.2?+
Neither has a larger sourced maximum output. Kimi K2.7 Code is — and GLM 5.2 is —.
Do Kimi K2.7 Code and GLM 5.2 support reasoning and tool use?+
Kimi K2.7 Code: reasoning, tool calling, and image input. GLM 5.2: reasoning and tool calling. Feature support does not establish relative quality.
Which is available from more inference providers, Kimi K2.7 Code or GLM 5.2?+
Kimi K2.7 Code has 4 sourced provider routes; GLM 5.2 has 5, so GLM 5.2 has broader tracked availability.
Which offers better value, Kimi K2.7 Code or GLM 5.2?+
There is no universal value winner. Compare the input and output prices above with the matched benchmark result for your workload: cheaper tokens can be offset by different quality, token usage, latency, or provider availability.