Claude Haiku 4.5 vs GLM-4.6V-Flash vs GLM-4.7

GLM-4.6V-Flash is the better all-round choice, scoring 63/100 against Claude Haiku 4.5 (47) and GLM-4.7 (41). It leads on price. Claude Haiku 4.5 wins on inputs & features. The score weighs price 50%, inputs & features 30%, context window 20%. None of the shared benchmarks cover every model here yet, so capability is left out of this verdict.

GLM-4.6V-Flash is cheaper at $0.161 input / $0.559 output per million tokens (median across 2 API providers; free on Z.AI). GLM-4.7 costs $0.60 input / $2.20 output per million tokens (official Z.AI API price); Claude Haiku 4.5 costs $1.00 input / $5.00 output per million tokens (official Anthropic API price). At a typical mix of three input tokens to one output token, that is $0.261 per million tokens for GLM-4.6V-Flash versus $1.00 for GLM-4.7 (3.8× as much) and $2.00 for Claude Haiku 4.5 (7.7× as much).

There is no independent benchmark that covers all three models yet. Claude Haiku 4.5 has an ECI of 142.2, GLM-4.6V-Flash has not been scored yet and GLM-4.7 has an ECI of 143.7.

There are no published SWE-bench Verified results for Claude Haiku 4.5, GLM-4.6V-Flash and GLM-4.7 yet, so there is no like-for-like coding score. Test both on a sample of your own tasks. All three support tool calling for agent workflows.

GLM-4.7 has the largest context window at 204,800 tokens, against 200,000 for Claude Haiku 4.5 and 128,000 for GLM-4.6V-Flash. Maximum output per response: Claude Haiku 4.5 up to 64,000, GLM-4.6V-Flash up to 32,768, GLM-4.7 up to 131,072 tokens.

Claude Haiku 4.5 accepts text, images and PDFs; GLM-4.6V-Flash accepts text, images and video; GLM-4.7 accepts text. Claude Haiku 4.5 handles the widest range of inputs.

GLM-4.6V-Flash and GLM-4.7 publishes its weights and can be self-hosted; Claude Haiku 4.5 is proprietary.

GLM-4.7 is the newest, released Dec 22, 2025. GLM-4.6V-Flash came out Dec 8, 2025; Claude Haiku 4.5 came out Oct 15, 2025. Knowledge cutoff: Claude Haiku 4.5 Feb 28, 2025, GLM-4.7 Apr 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 Nov 2, 2026.