GPT-5.4 mini vs GLM-5 vs Grok 4.3

Grok 4.3 is the better all-round choice, scoring 67/100 against GPT-5.4 mini (63) and GLM-5 (55). It leads on inputs & features and context window. The score weighs capability 50%, price 25%, inputs & features 15%, context window 10%.

GLM-5 is cheaper at $1.00 input / $3.20 output per million tokens (official Z.AI API price). Grok 4.3 costs $1.25 input / $2.50 output per million tokens (official xAI API price); GPT-5.4 mini costs $0.75 input / $4.50 output per million tokens (official OpenAI API price). At a typical mix of three input tokens to one output token, that is $1.55 per million tokens for GLM-5 versus $1.56 for Grok 4.3 (1× as much) and $1.69 for GPT-5.4 mini (1.1× as much).

Grok 4.3 scores higher on the Capabilities Index (ECI): Grok 4.3 149.2 (#55 of 148), GPT-5.4 mini 148.8 (#56 of 148) and GLM-5 145.8 (#74 of 148). The confidence ranges of the top two overlap (147.6–150.8 vs 147.1–150.5), so treat the gap as small. On individual benchmarks: GPQA Diamond — Grok 4.3 88.8%, GLM-5 87.8%, GPT-5.4 mini 86.9%; OTIS Mock AIME 2024–2025 — Grok 4.3 93.3%, GPT-5.4 mini 88.9%, GLM-5 80.0%.

There are no published SWE-bench Verified results for GPT-5.4 mini and Grok 4.3 yet, so there is no like-for-like coding score. On overall capability, Grok 4.3 leads, which tends to carry over to coding, but test on your own codebase. All three support tool calling for agent workflows.

Grok 4.3 has the largest context window at 1,000,000 tokens, against 400,000 for GPT-5.4 mini and 204,800 for GLM-5. Maximum output per response: GPT-5.4 mini up to 128,000, GLM-5 up to 131,072, Grok 4.3 up to 30,000 tokens.

GPT-5.4 mini accepts text and images; GLM-5 accepts text; Grok 4.3 accepts text, images and PDFs. Grok 4.3 handles the widest range of inputs.

GLM-5 publishes its weights and can be self-hosted; GPT-5.4 mini and Grok 4.3 is proprietary.

Grok 4.3 is the newest, released Apr 17, 2026. GPT-5.4 mini came out Mar 17, 2026; GLM-5 came out Feb 12, 2026. Knowledge cutoff: GPT-5.4 mini Aug 31, 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.