GLM-5.3-Flash vs Grok 4.6

GLM-5.3-Flash is the better all-round choice, scoring 80/100 against Grok 4.6 (65). It leads on price, inputs & features and context window. Grok 4.6 wins on capability. The score weighs capability 50%, price 25%, inputs & features 15%, context window 10%.

GLM-5.3-Flash is cheaper at $0.15 input / $0.50 output per million tokens (official Z.AI API price). Grok 4.6 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 4.6 (13× as much).

Grok 4.6 scores higher on the Capabilities Index (ECI): Grok 4.6 156.6 (#19 of 148) and GLM-5.3-Flash 151.9 (#42 of 148). Their confidence ranges do not overlap (154.7–158.9 vs 149.4–154.3), so the gap is a real one. On individual benchmarks: GPQA Diamond — Grok 4.6 94.0%, GLM-5.3-Flash 90.2%; FrontierMath Tiers 1–3 — Grok 4.6 66.0%, GLM-5.3-Flash 55.8%; OTIS Mock AIME 2024–2025 — Grok 4.6 99.2%, GLM-5.3-Flash 93.9%.

There are no published SWE-bench Verified results for GLM-5.3-Flash and Grok 4.6 yet, so there is no like-for-like coding score. On overall capability, Grok 4.6 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 4.6. Maximum output per response: GLM-5.3-Flash up to 131,072, Grok 4.6 up to 500,000 tokens.

GLM-5.3-Flash accepts text, images, PDFs and video; Grok 4.6 accepts text and images. GLM-5.3-Flash handles the widest range of inputs.

GLM-5.3-Flash publishes its weights and can be self-hosted; Grok 4.6 is proprietary.

GLM-5.3-Flash is the newest, released Aug 26, 2026. Grok 4.6 came out Aug 12, 2026. Knowledge cutoff: Grok 4.6 Feb 1, 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.