GLM-5.1 vs Qwen3.6-35B-A3B
GLM-5.1 leads the LLM Stats Score 38.9 to 32.2. Qwen3.6-35B-A3B is 5.3x cheaper per token.
Zhipu AI · Alibaba Cloud / Qwen Team · Updated for 2026
Which is better?
GLM-5.1 leads the overall LLM Stats Score 38.9 to 32.2, ranking #77 overall.
In the 12 individual benchmarks reported for both models, GLM-5.1 wins 11; this is a narrower head-to-head signal than the composite indexes.
On price, Qwen3.6-35B-A3B is roughly 5.3x cheaper per token on a blended 3:1 input/output basis, which adds up quickly at production volume.
Qwen3.6-35B-A3B also accepts a larger context window (262,144 input tokens), making it the stronger choice for long documents and large codebases.
Based on current LLM Stats indexes, shared benchmarks, pricing, and model metadata for 2026.
Choose GLM-5.1
- overall performance matters — it scores 38.9 and ranks #77 on LLM Stats
- your work emphasizes reasoning and coding — it leads those capability indexes
- you value its reported benchmark strengths — it wins 11 of 12 exact shared results
Choose Qwen3.6-35B-A3B
- cost matters — it's about 5.3x cheaper per token
- you process long inputs — it offers a 262,144 token context window
- you want the most recent training data — it shipped Apr 2026
At a glance
The differences that matter most.
Capability indexes
Additional strengths measured across groups of related public benchmarks
Individual benchmarks
18 reported for GLM-5.1 · 49 for Qwen3.6-35B-A3B
GLM-5.1 outperforms in 11 benchmarks (AIME 2026, GPQA, HMMT 2025, Humanity's Last Exam, IMO-AnswerBench, MCP Atlas, NL2Repo, SWE-Bench Pro, TAU3-Bench, Terminal-Bench 2.0, Toolathlon), while Qwen3.6-35B-A3B is better at 1 benchmark (HMMT Feb 26).
GLM-5.1 significantly outperforms across most benchmarks.
Human preference
Blind head-to-head votes and playground preference scores
Pricing Analysis
Price comparison per million tokens
For input processing, GLM-5.1 ($1.05/1M tokens) is 10.5x more expensive than Qwen3.6-35B-A3B ($0.10/1M tokens).
For output processing, GLM-5.1 ($3.50/1M tokens) is 3.7x more expensive than Qwen3.6-35B-A3B ($0.95/1M tokens).
In conclusion, GLM-5.1 is more expensive than Qwen3.6-35B-A3B.*
* Using a 3:1 ratio of input to output tokens
Model Size
Parameter count comparison
GLM-5.1 has 719.0B more parameters than Qwen3.6-35B-A3B, making it 2054.3% larger.
Context Window
Maximum input and output token capacity
Qwen3.6-35B-A3B accepts 262,144 input tokens compared to GLM-5.1's 202,752 tokens. Qwen3.6-35B-A3B can generate longer responses up to 262,144 tokens, while GLM-5.1 is limited to 202,752 tokens.
Input capabilities
Documented input modalities across available providers
Qwen3.6-35B-A3B supports multimodal inputs, whereas GLM-5.1 does not.
Qwen3.6-35B-A3B can handle both text and other forms of data like images, making it suitable for multimodal applications.
GLM-5.1
Qwen3.6-35B-A3B
License
Usage and distribution terms
GLM-5.1 is licensed under MIT, while Qwen3.6-35B-A3B uses Apache 2.0.
License differences may affect how you can use these models in commercial or open-source projects.
MIT
Open weights
Apache 2.0
Open weights
Release Timeline
When each model was launched
GLM-5.1 was released on 2026-04-07, while Qwen3.6-35B-A3B was released on 2026-04-16.
Qwen3.6-35B-A3B is 0 month newer than GLM-5.1.
Apr 7, 2026
6 months ago
Apr 16, 2026
6 months ago
1w newerKnowledge Cutoff
When training data ends
Neither model specifies a knowledge cutoff date.
Unable to compare the recency of their training data.
Provider Availability
GLM-5.1 is available from DeepInfra, FriendliAI, ZAI. Qwen3.6-35B-A3B is available from DeepInfra.
GLM-5.1
Qwen3.6-35B-A3B
Outputs Comparison
Judge for yourself.
Run your own prompts against GLM-5.1 and Qwen3.6-35B-A3B side-by-side, then vote on the output you prefer.
FAQ
Common questions about GLM-5.1 vs Qwen3.6-35B-A3B.