GLM-5.2 is Z.ai’s flagship model for the era of long-horizon tasks. With a truly usable 1M-token context window, it can handle project-level engineering context, execute long-running tasks more reliably, follow engineering standards more consistently, and complete the full development workflow from requirements to multi-platform deployment in a single task.
GLM 5.2 vs gpt-oss-120b
Compare GLM 5.2 from Z.AI and gpt-oss-120b from OpenAI on key metrics including benchmarks, price, context length, and other model features. Access both models and hundreds of others through the AIHubMix API.
GLM 5.2gpt-oss-120b is a 117B-parameter open-weight Mixture-of-Experts (MoE) language model from OpenAI, designed for high-reasoning, agentic, and general-purpose production use cases. Activating just 5.1B parameters per pass, it is optimized to run on a single H100 GPU with native MXFP4 quantization. The model features configurable reasoning depth, full chain-of-thought access, and native tool use, including function calling, browsing, and structured output generation.
Pricing & Specifications
Prices are per million tokens. Time to First Token and throughput are rolling averages measured on AIHubMix.
Promotional prices show the discounted rate; see each model page for promotion windows.
Activity Past 30 Days
Daily traffic served through AIHubMix — how demand for each model is trending.
Tokens / day
Requests / day
Performance Past 3 Days
Measured on real AIHubMix traffic, hourly buckets. Gaps mean no traffic in that hour.
Throughput (tok/s)
TTFT (s)
Uptime (%)
LMArena Benchmarks
LMArena ratings by capability (Bradley-Terry, commonly called Elo). Higher is better.
Source: LMArena (arena.ai) leaderboard, imported by AIHubMix. Models without published ratings are omitted per chart.
Cost calculator
Estimate your monthly bill for the same workload on each model.
Monthly = daily × 30. Discounted rates applied where a promotion is active.
FAQ
Which is cheaper: GLM 5.2, gpt-oss-120b?
gpt-oss-120b: $0.90/M output tokens; GLM 5.2: $3.94/M. Use the cost calculator above to estimate your own workload.
How do their coding arena scores compare?
GLM 5.2: 1505; gpt-oss-120b: 1390 (LMArena coding leaderboard).
Which responds faster?
gpt-oss-120b: 0.2s time to first token measured on AIHubMix; see the live performance charts above for how each model behaves across the day.
How large is each context window?
GLM 5.2 accepts 1,000,000 and gpt-oss-120b accepts 131,072 input tokens. Maximum output per request is 128,000 tokens on GLM 5.2 and 32,768 tokens on gpt-oss-120b.
Which one generates tokens faster?
gpt-oss-120b at 1101.0 tok/s and GLM 5.2 at 37.5 tok/s, measured as output throughput on AIHubMix — a separate metric from time to first token.
What inputs and capabilities does each model support?
GLM 5.2 accepts text input and supports thinking, tool calling, function calling and structured outputs; gpt-oss-120b accepts text input and supports thinking, function calling and structured outputs.
Can I call GLM 5.2 and gpt-oss-120b with the same API key?
Yes. AIHubMix serves every model on this page behind one OpenAI-compatible endpoint, so switching between them is a one-line change to the model field — no second account, key or SDK.
Popular comparisons
Related model match-ups readers also look at.
