API cost decision in 10 seconds

Qwen3 VL 235B A22B Thinking vs GLM 4.6

Pick GLM 4.6 when budget and context both matter.

Page updated:  Data confirmed:  Prices normalized to USD per 1M tokens Sample workload: 1M input + 500K output

Budget verdict

Pick GLM 4.6 when budget and context both matter.

On the standard 1M input plus 500K output workload, GLM 4.6 is estimated at $1.3 vs $1.56 for Qwen3 VL 235B A22B Thinking, saving $0.26 (16.7% lower).

Cost-first pickGLM 4.6
Context-first pickGLM 4.6
Sample savings$0.2616.7%
10x traffic gap$2.6

GLM 4.6 is cheaper on the standard workload and also has the larger context window. At 10x that traffic, the same price gap is about $2.6. Use the calculator below to replace the sample workload with your own token volume.

Cost sensitivity

Workload Sensitivity

Same prices, different token mixes.

Cost winner changes by workload shape: input-heavy / RAG favors Qwen3 VL 235B A22B Thinking, balanced workload favors GLM 4.6, and output-heavy chatbot favors GLM 4.6.

Workload shapeToken mixBetter pickQwen3 VL 235B A22B ThinkingGLM 4.6
Input-heavy / RAG5M input + 500K outputQwen3 VL 235B A22B Thinking$2.6$3.02
Balanced workload1M input + 1M outputGLM 4.6$2.86$2.17
Output-heavy chatbot1M input + 5M outputGLM 4.6$13.26$9.13
Cheaper input Qwen3 VL 235B A22B Thinking $0.26 vs $0.43 / 1M

Qwen3 VL 235B A22B Thinking is $0.17 cheaper per 1M input tokens (39.5% lower; 1.65x difference).

Cheaper output GLM 4.6 $2.6 vs $1.74 / 1M

GLM 4.6 is $0.86 cheaper per 1M output tokens (33.1% lower; 1.49x difference).

Larger context GLM 4.6 131.07K vs 202.75K

GLM 4.6 has 71.68K more context (1.55x larger).

Sample workload GLM 4.6 $1.56 vs $1.3

GLM 4.6 is $0.26 cheaper on the standard workload (16.7% lower).

Estimate your workload cost

Your Workload Cost

Prices are normalized to USD per 1M tokens.
Qwen3 VL 235B A22B Thinking Calculating… Estimated API cost
GLM 4.6 Calculating… Estimated API cost
Cheaper for this workload Calculating… Difference: calculating…

This estimate uses normalized public API pricing per 1M tokens. It is a planning aid, not a billing quote. Verify provider pricing, limits, and terms before production use.

Quick Decision

Verdict

Qwen3 VL 235B A22B Thinking has the lower input price; GLM 4.6 has the lower output price; GLM 4.6 offers the larger context window. For the 1M input plus 500K output sample, GLM 4.6 is cheaper for the standard workload.

For a 1M input token plus 500K output token workload, the estimated API cost is $1.56 for Qwen3 VL 235B A22B Thinking and $1.3 for GLM 4.6.

Best Fit

Choose Qwen3 VL 235B A22B Thinking when you care most about lower input-token price.

Choose GLM 4.6 when you care most about lower output-token price, and larger context window.

Decision Notes
  • On the standard 1M input plus 500K output workload, GLM 4.6 is estimated at $1.3 vs $1.56 for Qwen3 VL 235B A22B Thinking, saving $0.26 (16.7% lower).
  • GLM 4.6 is $0.26 cheaper on the standard workload (16.7% lower).
  • Qwen3 VL 235B A22B Thinking is $0.17 cheaper per 1M input tokens (39.5% lower; 1.65x difference).
  • GLM 4.6 is $0.86 cheaper per 1M output tokens (33.1% lower; 1.49x difference).
  • GLM 4.6 has 71.68K more context (1.55x larger).
Head-to-Head Specs
FeatureQwen3 VL 235B A22B Thinking
(Qwen)		GLM 4.6
(Z.ai)
Input Price
prompt tokens per 1M		$0.26$0.43
Completion Price
per 1M tokens		$2.6$1.74
Sample Workload Cost
1M input + 500K output		$1.56$1.3
Context Window131.07K202.75K
Release Date
Popularity#103#122

Use-Case Decision Matrix

Use caseBetter pickWhy
Budget-constrained productionGLM 4.6On the standard 1M input plus 500K output workload, GLM 4.6 is estimated at $1.3 vs $1.56 for Qwen3 VL 235B A22B Thinking, saving $0.26 (16.7% lower).
High-volume input processingQwen3 VL 235B A22B ThinkingLower prompt-token price matters most when prompts, retrieved passages, or documents dominate the bill.
Long responses and chatbotsGLM 4.6Lower output-token price matters most when assistants generate many completion tokens.
RAG or long-document workGLM 4.6A larger context window leaves more room for retrieved passages, conversation history, or source files.

Related Alternatives

Same-provider lower-cost swaps
  • Qwen3 Next 80B A3B Instruct (free) can replace Qwen3 VL 235B A22B Thinking when lower sample workload cost matters most: $0.
  • Qwen3 Coder 480B A35B (free) can replace Qwen3 VL 235B A22B Thinking when lower sample workload cost matters most: $0.
  • Qwen2.5 7B Instruct can replace Qwen3 VL 235B A22B Thinking when lower sample workload cost matters most: $0.09.
  • Qwen3.5-9B can replace Qwen3 VL 235B A22B Thinking when lower sample workload cost matters most: $0.11.
Larger context near this budget
  • Llama 4 Scout offers 10M context with $0.23 sample workload cost.
  • Owl Alpha offers 1.05M context with $0 sample workload cost.
  • MiMo-V2.5 offers 1.05M context with $0.28 sample workload cost.
  • DeepSeek V4 Flash offers 1.05M context with $0.2 sample workload cost.

Cheaper alternatives

Review low-cost models sorted by a standard 1M input plus 500K output workload.

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Larger context alternatives

Find models with larger context windows for RAG, long documents, and codebase review.

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Provider catalogs

Compare models within provider hubs before choosing a final API vendor.

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Qwen catalog

Review all tracked Qwen models before deciding whether this matchup is the right shortlist.

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Z.ai catalog

Check other Z.ai models with comparable pricing, context, or release timing.

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Qwen3 VL 235B A22B Thinking

Qwen3-VL-235B-A22B Thinking is a multimodal model that unifies strong text generation with visual understanding across images and video. The Thinking model is optimized for multimodal reasoning in STEM and math....

GLM 4.6

Compared with GLM-4.5, this generation brings several key improvements: Longer context window: The context window has been expanded from 128K to 200K tokens, enabling the model to handle more complex...