Head to Head

zai-org/GLM-5.1 vs Qwen/Qwen3.6-35B-A3B

Pricing, experience, and what the community actually says.

zai-org/GLM-5.1

zai-org/GLM-5.1

Starting at

$1.40 / 1M input tokens

Refund

Pay-as-you-go model; no refunds on consumed tokens. Unused credits may expire per provider terms.

Try Free →

★ Our Pick

Qwen/Qwen3.6-35B-A3B

Qwen/Qwen3.6-35B-A3B

Starting at

Free (self-hosted)

Refund

N/A (Open-source model; cloud API providers follow their own terms)

Try Free →

Our Take

zai-org/GLM-5.1zai-org/GLM-5.1

Worth it for developers and enterprises needing a highly capable, commercially permissive model for software engineering and complex multi-step agents, provided latency and token costs fit the budget.

GLM-5.1 delivers frontier-level reasoning and coding performance under an open MIT license, but its high token cost and slower inference speed make it best suited for specialized, high-value tasks rather than high-volume, low-latency applications.

Qwen/Qwen3.6-35B-A3BQwen/Qwen3.6-35B-A3B

Yes, particularly for teams needing a cost-effective, self-hostable model with robust tool-calling and long-context capabilities.

Qwen3.6-35B-A3B delivers strong agentic coding and multimodal reasoning at a fraction of the cost of frontier closed models, making it a practical choice for developers prioritizing efficiency and open licensing.

Pros & Cons

zai-org/GLM-5.1

Strong multi-step reasoning and coding performance
Commercially permissive MIT license
Large 200k context window
Open-weight with transparent architecture
High benchmark scores (Intelligence Index: 51)
Higher token pricing compared to many open models
Slower inference speed (~44 t/s)
High verbosity increases output costs
Text-only input/output requires separate vision models
Heavy hardware requirements for self-hosting

Qwen/Qwen3.6-35B-A3B

Highly cost-effective API pricing
Apache 2.0 commercial license
Efficient inference with 3B active parameters
Strong agentic coding and tool-calling performance
262k context window for long documents/codebases
Slightly lower composite intelligence scores than top-tier proprietary models
Requires adequate GPU VRAM for local deployment
Math and advanced reasoning benchmarks trail behind flagship models
Community support only for self-hosted setups

Full Breakdown

Category
zai-org/GLM-5.1zai-org/GLM-5.1
Qwen/Qwen3.6-35B-A3BQwen/Qwen3.6-35B-A3B

Overall Rating

4.2 / 5
4.3 / 5

Starting Price

$1.40 / 1M input tokens
Free (self-hosted)

Learning Curve

Moderate. Requires familiarity with OpenAI-compatible SDKs, prompt engineering for reasoning modes, and token budget management due to verbosity.
Moderate; familiar to developers using OpenAI-compatible clients, but tuning MoE routing and thinking modes requires some experimentation.

Best Suited For

Software engineering teams, AI agent developers, and researchers requiring strong multi-step reasoning and open-weight deployment flexibility.
Software developers, AI engineers, and researchers building agentic workflows, code assistants, or multimodal applications on a budget.

Support Quality

Standard developer documentation and community support via GitHub and Hugging Face. No dedicated enterprise SLA is publicly advertised for the open-weight version.
Community-driven via GitHub, Discord, and Hugging Face; enterprise support available through Alibaba Cloud.

Hidden Costs

High verbosity can significantly increase output token consumption. Self-hosting requires substantial GPU infrastructure due to the 754B parameter size.
Compute costs for self-hosting (GPU memory, electricity) and potential third-party API markups.

Refund Policy

Pay-as-you-go model; no refunds on consumed tokens. Unused credits may expire per provider terms.
N/A (Open-source model; cloud API providers follow their own terms)

Platforms

Cloud API, Self-hosted (GPU), Hugging Face, ModelScope
Linux, macOS, Windows, Cloud APIs, Docker

Features

Watermark on Free Plan

✗ No
✗ No

Mobile App

✗ No
✗ No

API Access

✓ Yes
✓ Yes