GLM-5.3 vs GPT-5.6 Terra

GPT-5.6 Terra is the better all-round choice, scoring 67/100 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-5.6 Terra costs $2.00 input / $12.00 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 $4.50 for GPT-5.6 Terra (2.1× as much).

GPT-5.6 Terra scores higher on the Capabilities Index (ECI): GPT-5.6 Terra 160.1 (#15 of 165) and GLM-5.3 156.2 (#33 of 165). The confidence ranges of the top two overlap (157.8–163.4 vs 154.3–158.5), so treat the gap as small. On individual benchmarks: GPQA Diamond — GPT-5.6 Terra 93.3%, GLM-5.3 90.9%; FrontierMath Tiers 1–3 — GPT-5.6 Terra 86.0%, GLM-5.3 68.8%; OTIS Mock AIME 2024–2025 — GPT-5.6 Terra 99.7%, GLM-5.3 91.1%; SimpleQA Verified — GPT-5.6 Terra 43.2%, GLM-5.3 41.0%.

There are no published SWE-bench Verified results for GLM-5.3 and GPT-5.6 Terra yet, so there is no like-for-like coding score. On overall capability, GPT-5.6 Terra leads, which tends to carry over to coding, but test on your own codebase. Both support tool calling for agent workflows.

GPT-5.6 Terra 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-5.6 Terra up to 128,000 tokens.

GLM-5.3 accepts text; GPT-5.6 Terra accepts text, images and PDFs. GPT-5.6 Terra handles the widest range of inputs.

GLM-5.3 publishes its weights and can be self-hosted; GPT-5.6 Terra is proprietary.

GLM-5.3 is the newest, released Aug 14, 2026. GPT-5.6 Terra came out Jul 9, 2026. Knowledge cutoff: GPT-5.6 Terra Feb 16, 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.