GLM-4.7 vs GPT-5 Chat vs Qwen MT Plus

GLM-4.7 is the better all-round choice, scoring 41/100 against GPT-5 Chat (31) and Qwen MT Plus (11). It leads on price. GPT-5 Chat wins on context window. The score weighs price 50%, inputs & features 30%, context window 20%. None of the shared benchmarks cover every model here yet, so capability is left out of this verdict.

GLM-4.7 is cheaper at $0.60 input / $2.20 output per million tokens (official Z.AI API price). GPT-5 Chat costs $1.25 input / $10.00 output per million tokens (median across 5 API providers); Qwen MT Plus costs $2.46 input / $7.37 output per million tokens (official Alibaba API price). At a typical mix of three input tokens to one output token, that is $1.00 per million tokens for GLM-4.7 versus $3.44 for GPT-5 Chat (3.4× as much) and $3.69 for Qwen MT Plus (3.7× as much).

There is no independent benchmark that covers all three models yet. GLM-4.7 has an ECI of 143.7, GPT-5 Chat has not been scored yet and Qwen MT Plus has not been scored yet.

There are no published SWE-bench Verified results for GLM-4.7, GPT-5 Chat and Qwen MT Plus yet, so there is no like-for-like coding score. Test both on a sample of your own tasks. Note that GPT-5 Chat and Qwen MT Plus does not support tool calling, which most coding agents need.

GPT-5 Chat has the largest context window at 400,000 tokens, against 204,800 for GLM-4.7 and 16,384 for Qwen MT Plus. Maximum output per response: GLM-4.7 up to 131,072, GPT-5 Chat up to 128,000, Qwen MT Plus up to 8,192 tokens.

GLM-4.7 accepts text; GPT-5 Chat accepts text and images; Qwen MT Plus accepts text. GPT-5 Chat handles the widest range of inputs.

GLM-4.7 publishes its weights and can be self-hosted; GPT-5 Chat and Qwen MT Plus is proprietary.

GLM-4.7 is the newest, released Dec 22, 2025. GPT-5 Chat came out Aug 7, 2025; Qwen MT Plus came out Jul 24, 2025. Knowledge cutoff: GLM-4.7 Apr 2025, GPT-5 Chat Sep 30, 2024.

Each model gets a 0–100 score on capability (50%, independent benchmark results); price (25%, blended price per million tokens (3 input : 1 output), log scale); inputs & features (15%, image, PDF, audio and video input, tool calling, structured output and reasoning); context window (10%, maximum tokens per request, log scale). Dimensions missing for any model are dropped and the remaining weights rescaled, so every model is judged on the same evidence. Specs and prices come from public model listings and the labs’ own API pages; capability scores come from independent benchmark runs. Data updated Nov 2, 2026.