GLM-5.3 vs Qwen3.8 27B vs Muse Spark 1.2

Muse Spark 1.2 is the better all-round choice, scoring 72/100 against Qwen3.8 27B (67) and GLM-5.3 (64). It leads on inputs & features. Qwen3.8 27B wins on price. The score weighs capability 50%, price 25%, inputs & features 15%, context window 10%.

Qwen3.8 27B is cheaper at $0.40 input / $2.50 output per million tokens (median across 39 API providers). Muse Spark 1.2 costs $1.25 input / $4.25 output per million tokens (official Meta API price); GLM-5.3 costs $1.40 input / $4.40 output per million tokens (official Z.AI API price). At a typical mix of three input tokens to one output token, that is $0.925 per million tokens for Qwen3.8 27B versus $2.00 for Muse Spark 1.2 (2.2× as much) and $2.15 for GLM-5.3 (2.3× as much).

GLM-5.3 scores higher on the Capabilities Index (ECI): GLM-5.3 155.8 (#24 of 148), Muse Spark 1.2 155.0 (#30 of 148) and Qwen3.8 27B 149.4 (#53 of 148). The confidence ranges of the top two overlap (153.7–158.3 vs 152.8–157.5), so treat the gap as small.

There are no published SWE-bench Verified results for GLM-5.3, Qwen3.8 27B and Muse Spark 1.2 yet, so there is no like-for-like coding score. On overall capability, GLM-5.3 leads, which tends to carry over to coding, but test on your own codebase. All three support tool calling for agent workflows.

Muse Spark 1.2 has the largest context window at 1,048,576 tokens, against 1,000,000 for GLM-5.3 and 262,144 for Qwen3.8 27B. Maximum output per response: GLM-5.3 up to 131,072, Qwen3.8 27B up to 32,768, Muse Spark 1.2 up to 131,072 tokens.

GLM-5.3 accepts text; Qwen3.8 27B accepts text, images and video; Muse Spark 1.2 accepts text, images, PDFs, audio and video. Muse Spark 1.2 handles the widest range of inputs.

GLM-5.3 and Qwen3.8 27B publishes its weights and can be self-hosted; Muse Spark 1.2 is proprietary.

GLM-5.3 is the newest, released Aug 14, 2026. Qwen3.8 27B came out Aug 14, 2026; Muse Spark 1.2 came out Aug 5, 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.