GLM-5.3-Flash vs Grok 4.7

GLM-5.3-Flash is the better all-round choice, scoring 79/100 against Grok 4.7 (64). It leads on price, inputs & features and context window. The score weighs capability 50%, price 25%, inputs & features 15%, context window 10%. Capability uses the average of shared benchmarks (GPQA Diamond, FrontierMath Tiers 1–3 and OTIS Mock AIME 2024–2025), because Grok 4.7 has no Capabilities Index score yet.

GLM-5.3-Flash is cheaper at $0.15 input / $0.50 output per million tokens (official Z.AI API price). Grok 4.7 costs $2.00 input / $6.00 output per million tokens (official xAI API price). At a typical mix of three input tokens to one output token, that is $0.237 per million tokens for GLM-5.3-Flash versus $3.00 for Grok 4.7 (13× as much).

Not every model here has a Capabilities Index score, so we compare the average of shared benchmarks (GPQA Diamond, FrontierMath Tiers 1–3 and OTIS Mock AIME 2024–2025): Grok 4.7 81.3% and GLM-5.3-Flash 79.9%. On individual benchmarks: GPQA Diamond — Grok 4.7 92.7%, GLM-5.3-Flash 90.2%; FrontierMath Tiers 1–3 — GLM-5.3-Flash 55.8%, Grok 4.7 53.0%; OTIS Mock AIME 2024–2025 — Grok 4.7 98.1%, GLM-5.3-Flash 93.9%.

There are no published SWE-bench Verified results for GLM-5.3-Flash and Grok 4.7 yet, so there is no like-for-like coding score. On overall capability, Grok 4.7 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 500,000 for Grok 4.7. Maximum output per response: GLM-5.3-Flash up to 131,072, Grok 4.7 up to 500,000 tokens.

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

GLM-5.3-Flash publishes its weights and can be self-hosted; Grok 4.7 is proprietary.

Grok 4.7 is the newest, released Sep 21, 2026. GLM-5.3-Flash came out Aug 26, 2026. Knowledge cutoff: Grok 4.7 May 2026.

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.