GLM-5.3-Flash vs GLM-4.7-Flash

GLM-5.3-Flash is the better all-round choice, scoring 85/100 against GLM-4.7-Flash (48). It leads on capability, inputs & features and context window. GLM-4.7-Flash wins on price. The score weighs capability 50%, price 25%, inputs & features 15%, context window 10%. Capability uses the average of shared benchmarks (GPQA Diamond and OTIS Mock AIME 2024–2025), because GLM-4.7-Flash has no Capabilities Index score yet.

GLM-4.7-Flash is cheaper at $0.06 input / $0.40 output per million tokens (median across 13 API providers; free on Z.AI). GLM-5.3-Flash costs $0.15 input / $0.50 output per million tokens (official Z.AI API price). At a typical mix of three input tokens to one output token, that is $0.145 per million tokens for GLM-4.7-Flash versus $0.237 for GLM-5.3-Flash (1.6× as much).

Not every model here has a Capabilities Index score, so we compare the average of shared benchmarks (GPQA Diamond and OTIS Mock AIME 2024–2025): GLM-5.3-Flash 92.0% and GLM-4.7-Flash 35.1%. On individual benchmarks: GPQA Diamond — GLM-5.3-Flash 90.2%, GLM-4.7-Flash 45.1%; OTIS Mock AIME 2024–2025 — GLM-5.3-Flash 93.9%, GLM-4.7-Flash 25.0%.

There are no published SWE-bench Verified results for GLM-5.3-Flash and GLM-4.7-Flash yet, so there is no like-for-like coding score. On overall capability, GLM-5.3-Flash leads, which tends to carry over to coding, but test on your own codebase. Both support tool calling for agent workflows.

GLM-5.3-Flash has the largest context window at 1,000,000 tokens, against 200,000 for GLM-4.7-Flash. Maximum output per response: GLM-5.3-Flash up to 131,072, GLM-4.7-Flash up to 131,072 tokens.

GLM-5.3-Flash accepts text, images, PDFs and video; GLM-4.7-Flash accepts text. GLM-5.3-Flash handles the widest range of inputs.

Yes, both publish their weights, so you can self-host them.

GLM-5.3-Flash is the newest, released Aug 26, 2026. GLM-4.7-Flash came out Jan 19, 2026. Knowledge cutoff: GLM-4.7-Flash Apr 2025.

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 Oct 4, 2026.