Open flagship GLM for long-horizon coding agents and million-token context work
GLM-5.2 by zhipuai is offered by 103 providers on this page. Public prices are shown for 94 of them. Its official list price is $1.40 per 1M input tokens and $4.40 per 1M output tokens. The lowest paid channel is CrofAI at $0.30 / $1.05 per 1M, about 7.7× below the list price. That channel is a third-party gateway, so confirm its availability and rate limits before depending on it. It also has 4 free ($0) channels and 4 covered by a paid subscription; free tiers usually carry rate limits, and subscription-covered access bills $0 per token only after the subscription fee.
Artificial Analysis rates it 33.7 on the Intelligence Index, with 68.8 for coding and 38.4 for agentic tasks. Against its lowest blended price of $0.487 per 1M, that is roughly 69 index points per dollar, which is the value ratio the leaderboards rank on. Median output speed is 89 tokens per second, with 3.25s to the first token. Running one task of the Artificial Analysis suite costs about $1.4726, which reflects how many tokens its reasoning consumes rather than the unit price alone.
The context window is 1,000,000 tokens at the reference host, but hosts report different limits, from 96,000 to 1,049,000, so the usable window depends on the provider you pick. It supports reasoning, tool use, and structured output. Accepted input modalities are Text and Image. The weights are open, so it can also be self-hosted or served through a gateway of your choice. Providers report the capability flags inconsistently, so verify a specific feature against the host you plan to use.
Quality is independently evaluated by Artificial Analysis. Speed/latency are model-level medians.
| Provider | Tier | Input | Output | Cache read | Cache write | Context | Output limit | Status |
|---|---|---|---|---|---|---|---|---|
| SenseNova (China) | Gateway | Free | $0 | — | 1,000,000 | 131,072 | ||
| Alibaba Token Plan | Gateway | Subscription | $0 | $0 | 1,000,000 | 131,072 | ||
| Alibaba Token Plan (China) | Gateway | Subscription | $0 | $0 | 1,000,000 | 131,072 | ||
| UnoRouter glm-5.2:free | Gateway | Free | — | — | 1,000,000 | 131,072 | ||
| Z.AI Coding Plan | Gateway | Subscription | $0 | $0 | 1,000,000 | 131,072 | ||
| SCNet Token Plan GLM-5.2 | Gateway | Subscription | $0 | — | 1,000,000 | 131,072 | ||
| Nvidia | Cloud | Free | — | — | 1,000,000 | 131,072 | deprecated | |
| Kenari glm-5-2 | Gateway | Free | — | — | 1,000,000 | 131,072 | ||
| CrofAI | Gateway | $0.30 | $1.05 | $0.05 | — | 1,000,000 | 131,072 | |
| NanoGPT | Gateway | $0.42 | $1.32 | $0.078 | — | 1,048,576 ⚠ | 131,072 | |
| Z.AIOfficial | First-party | $1.40 | $4.40 | $0.26 | $0 | 1,000,000 | 131,072 | |
Sorted by blended price (input×0.75 + output×0.25) asc. The official channel always shows regardless of rank. Whether a gateway's low price is actually usable can't be verified.
Interleaved thinking (reasoning between tool calls) is declared by 65 of 103 providers.
13 / 103 providers expose no reasoning control (reasoning_options: []).
8 more channels offer $0 (SenseNova (China), Alibaba Token Plan, Alibaba Token Plan (China) etc.); free tiers usually have rate limits and no SLA, excluded from ranking.
| Name | Conditions | Score | Metric | Source |
|---|---|---|---|---|
| SWE-Bench Pro | — | 62.1 | resolve rate | Source ↗ |
| Terminal-Bench | harness: Claude Code · v2.1 | 82.7 | success rate | Source ↗ |
| FrontierSWE | — | 74.4 | dominance | Source ↗ |
| Humanity's Last Exam | dataset: text-only subset | 40.5 | accuracy | Source ↗ |
| Humanity's Last Exam | variant: with tools · dataset: text-only subset | 54.7 | accuracy | Source ↗ |
| CritPt | — | 20.9 | accuracy | Source ↗ |
| AIME | v2026 | 99.2 | accuracy | Source ↗ |
| HMMT | vNovember 2025 | 94.4 | accuracy | Source ↗ |
| HMMT | vFebruary 2026 | 92.5 | accuracy | Source ↗ |
| IMOAnswerBench | — | 91 | accuracy | Source ↗ |
| GPQA Diamond | — | 91.2 | accuracy | Source ↗ |
| NL2Repo | — | 48.9 | resolve rate | Source ↗ |
| DeepSWE | — | 46.2 | resolve rate | Source ↗ |
| Program Bench | — | 63.7 | score | Source ↗ |
| Terminal-Bench | harness: Terminus 2 · v2.1 | 81 | success rate | Source ↗ |
| PostTrainBench | — | 34.3 | score | Source ↗ |
| SWE Marathon | — | 13 | resolve rate | Source ↗ |
| MCP Atlas | dataset: public subset | 76.8 | score | Source ↗ |
| Tool-Decathlon | — | 48.2 | score | Source ↗ |
The same benchmark scores very differently across harness / dataset, so the qualifying conditions must be shown together.
Individual evaluations run by Artificial Analysis, on the same reasoning tier as the intelligence score above. Each benchmark has its own task set and harness, so rows are not comparable with one another. The Intelligence Index above draws on a different, newer set of evaluations.