Compare AI models
| Specifications | ||
Context windowHow much information the model can work with in one request, measured in tokens — pieces of words or other data. This includes your question, attachments, conversation and reply. Limits can vary by model variant and provider. | 1M | 200k |
| API pricingUSD per 1M tokens · lower wins | ||
Input priceWhat you pay for everything you send the model — your question, plus any documents or earlier conversation you include with it. | — | $0.60 |
Output priceWhat you pay for the text the model writes back. It is normally the dearer half: producing an answer costs more than reading one. | — | $2.20 |
Cached input priceA reduced rate for text you send over and over. If every request starts with the same instructions or the same document, the provider keeps a copy ready and charges less to read it again. | — | $0.11 |
Cheapest inputLowest input rate across every provider on OpenRouter, the lab included. The cheapest endpoint may run a quantised build or a shorter context — see "Available from" on the model page. | — | $0.32DeepInfra |
Cheapest outputLowest output rate across every provider on OpenRouter, the lab included. May come from a different provider than the cheapest input. | — | $1.40DeepInfra |
| — | $168DeepInfra · fp4 | |
| These models have no shared benchmark scores. | ||
SWE-Bench VerifiedCoding — Real coding tasks pulled from open-source projects — the AI has to find and fix actual bugs. A human-checked version of the original SWE-Bench. Higher is better. | — | 73.8% |
LiveCodeBenchCompetitive coding — Coding problems published so recently the AI can't have seen them in training — a contamination-free test of raw programming skill. Higher is better. | — | 84.9% |
Terminal-Bench 2.0Agentic terminal coding — Can the AI work in a command-line terminal — running commands and finishing technical setup tasks the way a developer would? (Version 2.0 of the test.) Higher is better. | — | 41% |
BrowseCompWeb browsing — Can the AI browse the web and track down hard-to-find answers? Higher is better. | — | 52% |
Humanity's Last Exam · no toolsMultidisciplinary reasoning — Humanity's Last Exam — extremely hard expert questions across many subjects, written so you can't just look up the answer. “No tools” means the AI answers on its own. Higher is better. | — | 24.8% |
Humanity's Last Exam · with toolsMultidisciplinary reasoning — Humanity's Last Exam — extremely hard expert questions across many subjects. “With tools” means the AI is allowed to search the web or run code while answering. Higher is better. | — | 42.8% |
GPQA DiamondScience — Graduate-level science questions in biology, physics, and chemistry — hard enough that subject-matter PhDs score around 65%. Higher is better. | — | 85.7% |
| Overview | ||
| Company | Qwen | Z.ai |
| Release date | Nov 11 2026 | Dec 22 2025 |
| Access | Closed | Open Weight |
| Model details | View model | View model |
Other comparisons
Qwen4-Max PreviewvsClaude Fable 5.2GLM-4.7vsClaude Fable 5.2Qwen4-Max PreviewvsGPT-6.1 TerraGLM-4.7vsGPT-6.1 TerraQwen4-Max PreviewvsGemini 4 CarbonGLM-4.7vsGemini 4 CarbonQwen4-Max PreviewvsMuse EmberGLM-4.7vsMuse EmberQwen4-Max PreviewvsGrok 4.7GLM-4.7vsGrok 4.7Qwen4-Max PreviewvsDeepSeek-V4.1-Flash-1017GLM-4.7vsDeepSeek-V4.1-Flash-1017Frequently asked questions
Qwen4-Max Preview and GLM-4.7 don't publish scores on any of the same benchmarks, so there's no direct head-to-head comparison. Only GLM-4.7 has a verified first-party price for an available API: $0.60 per million input tokens and $2.20 per million output tokens. No currently available pay-as-you-go API rate is tracked for Qwen4-Max Preview. GLM-4.7 shipped 324 days before Qwen4-Max Preview, so benchmark comparisons should account for the intervening progress.
Context windows are 1M (Qwen4-Max Preview) vs 200k (GLM-4.7). Qwen4-Max Preview is closed, while GLM-4.7 is open weight.
Direct benchmark comparisons are unavailable — Qwen4-Max Preview and GLM-4.7 don't publish scores on any of the same benchmarks.