GLM-5.3 vs GPT-6 Astra

GPT-6 Astra is the better all-round choice, scoring 68/100 against GLM-5.3 (63). It leads on capability and inputs & features. GLM-5.3 wins on price. The score weighs capability 50%, price 25%, inputs & features 15%, context window 10%.

GLM-5.3 is cheaper at $1.40 input / $4.40 output per million tokens (official Z.AI API price). GPT-6 Astra costs $10.00 input / $50.00 output per million tokens (official OpenAI API price). At a typical mix of three input tokens to one output token, that is $2.15 per million tokens for GLM-5.3 versus $20.00 for GPT-6 Astra (9.3× as much).

GPT-6 Astra scores higher on the Capabilities Index (ECI): GPT-6 Astra 169.1 (#1 of 165) and GLM-5.3 156.2 (#33 of 165). Their confidence ranges do not overlap (165.9–174.3 vs 154.3–158.5), so the gap is a real one. On individual benchmarks: GPQA Diamond — GPT-6 Astra 95.8%, GLM-5.3 90.9%; FrontierMath Tiers 1–3 — GPT-6 Astra 93.7%, GLM-5.3 68.8%; OTIS Mock AIME 2024–2025 — GPT-6 Astra 100%, GLM-5.3 91.1%; SimpleQA Verified — GPT-6 Astra 75.6%, GLM-5.3 41.0%.

There are no published SWE-bench Verified results for GLM-5.3 and GPT-6 Astra yet, so there is no like-for-like coding score. On overall capability, GPT-6 Astra leads, which tends to carry over to coding, but test on your own codebase. Both support tool calling for agent workflows.

GPT-6 Astra has the largest context window at 1,050,000 tokens, against 1,000,000 for GLM-5.3. Maximum output per response: GLM-5.3 up to 131,072, GPT-6 Astra up to 128,000 tokens.

GLM-5.3 accepts text; GPT-6 Astra accepts text, images and PDFs. GPT-6 Astra handles the widest range of inputs.

GLM-5.3 publishes its weights and can be self-hosted; GPT-6 Astra is proprietary.

GPT-6 Astra is the newest, released Sep 4, 2026. GLM-5.3 came out Aug 14, 2026. Knowledge cutoff: GPT-6 Astra Apr 30, 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 Nov 2, 2026.