Model Comparison

Qwen2.5-Coder 32B Instruct vs Qwen3 VL 235B A22B Thinking

Qwen3 VL 235B A22B Thinking significantly outperforms across most benchmarks. Qwen2.5-Coder 32B Instruct is 13.4x cheaper per token.

Performance Benchmarks

Comparative analysis across standard metrics

3 benchmarks

Qwen2.5-Coder 32B Instruct outperforms in 0 benchmarks, while Qwen3 VL 235B A22B Thinking is better at 3 benchmarks (MMLU, MMLU-Pro, MMLU-Redux).

Qwen3 VL 235B A22B Thinking significantly outperforms across most benchmarks.

Thu May 14 2026 • llm-stats.com

Arena Performance

Human preference votes

Pricing Analysis

Price comparison per million tokens

Qwen2.5-Coder 32B Instruct costs less

For input processing, Qwen2.5-Coder 32B Instruct ($0.09/1M tokens) is 5.0x cheaper than Qwen3 VL 235B A22B Thinking ($0.45/1M tokens).

For output processing, Qwen2.5-Coder 32B Instruct ($0.09/1M tokens) is 38.8x cheaper than Qwen3 VL 235B A22B Thinking ($3.49/1M tokens).

In conclusion, Qwen3 VL 235B A22B Thinking is more expensive than Qwen2.5-Coder 32B Instruct.*

* Using a 3:1 ratio of input to output tokens

Lowest available price from all providers
Thu May 14 2026 • llm-stats.com
Alibaba Cloud / Qwen Team
Qwen2.5-Coder 32B Instruct
Input tokens$0.09
Output tokens$0.09
Best providerLambda
Alibaba Cloud / Qwen Team
Qwen3 VL 235B A22B Thinking
Input tokens$0.45
Output tokens$3.49
Best providerDeepinfra
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Model Size

Parameter count comparison

204.0B diff

Qwen3 VL 235B A22B Thinking has 204.0B more parameters than Qwen2.5-Coder 32B Instruct, making it 637.5% larger.

Alibaba Cloud / Qwen Team
Qwen2.5-Coder 32B Instruct
32.0Bparameters
Alibaba Cloud / Qwen Team
Qwen3 VL 235B A22B Thinking
236.0Bparameters
32.0B
Qwen2.5-Coder 32B Instruct
236.0B
Qwen3 VL 235B A22B Thinking

Context Window

Maximum input and output token capacity

Qwen3 VL 235B A22B Thinking accepts 262,144 input tokens compared to Qwen2.5-Coder 32B Instruct's 128,000 tokens. Qwen3 VL 235B A22B Thinking can generate longer responses up to 262,144 tokens, while Qwen2.5-Coder 32B Instruct is limited to 128,000 tokens.

Alibaba Cloud / Qwen Team
Qwen2.5-Coder 32B Instruct
Input128,000 tokens
Output128,000 tokens
Alibaba Cloud / Qwen Team
Qwen3 VL 235B A22B Thinking
Input262,144 tokens
Output262,144 tokens
Thu May 14 2026 • llm-stats.com

Input Capabilities

Supported data types and modalities

Qwen3 VL 235B A22B Thinking supports multimodal inputs, whereas Qwen2.5-Coder 32B Instruct does not.

Qwen3 VL 235B A22B Thinking can handle both text and other forms of data like images, making it suitable for multimodal applications.

Qwen2.5-Coder 32B Instruct

Text
Images
Audio
Video

Qwen3 VL 235B A22B Thinking

Text
Images
Audio
Video

License

Usage and distribution terms

Both models are licensed under Apache 2.0.

Both models share the same licensing terms, providing consistent usage rights.

Qwen2.5-Coder 32B Instruct

Apache 2.0

Open weights

Qwen3 VL 235B A22B Thinking

Apache 2.0

Open weights

Release Timeline

When each model was launched

Qwen2.5-Coder 32B Instruct was released on 2024-09-19, while Qwen3 VL 235B A22B Thinking was released on 2025-09-22.

Qwen3 VL 235B A22B Thinking is 12 months newer than Qwen2.5-Coder 32B Instruct.

Qwen2.5-Coder 32B Instruct

Sep 19, 2024

1.6 years ago

Qwen3 VL 235B A22B Thinking

Sep 22, 2025

7 months ago

1.0yr newer

Knowledge Cutoff

When training data ends

Neither model specifies a knowledge cutoff date.

Unable to compare the recency of their training data.

No cutoff dates available

Provider Availability

Qwen2.5-Coder 32B Instruct is available from Lambda, DeepInfra, Hyperbolic, Fireworks. Qwen3 VL 235B A22B Thinking is available from DeepInfra, Novita.

Qwen2.5-Coder 32B Instruct

lambda logo
Lambda
Input Price:Input: $0.09/1MOutput Price:Output: $0.09/1M
deepinfra logo
Deepinfra
Input Price:Input: $0.18/1MOutput Price:Output: $0.18/1M
hyperbolic logo
Hyperbolic
Input Price:Input: $0.20/1MOutput Price:Output: $0.20/1M
fireworks logo
Fireworks
Input Price:Input: $0.89/1MOutput Price:Output: $0.89/1M

Qwen3 VL 235B A22B Thinking

deepinfra logo
Deepinfra
Input Price:Input: $0.45/1MOutput Price:Output: $3.49/1M
novita logo
Novita
Input Price:Input: $0.98/1MOutput Price:Output: $3.95/1M
* Prices shown are per million tokens

Outputs Comparison

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Key Takeaways

Less expensive input tokens
Less expensive output tokens
Larger context window (262,144 tokens)
Supports multimodal inputs
Higher MMLU score (90.6% vs 75.1%)
Higher MMLU-Pro score (83.8% vs 50.4%)
Higher MMLU-Redux score (93.7% vs 77.5%)

Detailed Comparison

FAQ

Common questions about Qwen2.5-Coder 32B Instruct vs Qwen3 VL 235B A22B Thinking.

Which is better, Qwen2.5-Coder 32B Instruct or Qwen3 VL 235B A22B Thinking?

Qwen3 VL 235B A22B Thinking significantly outperforms across most benchmarks. Qwen2.5-Coder 32B Instruct is made by Alibaba Cloud / Qwen Team and Qwen3 VL 235B A22B Thinking is made by Alibaba Cloud / Qwen Team. The best choice depends on your use case — compare their benchmark scores, pricing, and capabilities above.

How does Qwen2.5-Coder 32B Instruct compare to Qwen3 VL 235B A22B Thinking in benchmarks?

Qwen2.5-Coder 32B Instruct scores HumanEval: 92.7%, GSM8k: 91.1%, MBPP: 90.2%, HellaSwag: 83.0%, Winogrande: 80.8%. Qwen3 VL 235B A22B Thinking scores ZebraLogic: 97.3%, DocVQAtest: 96.5%, ScreenSpot: 95.4%, CountBench: 93.7%, MMLU-Redux: 93.7%.

Is Qwen2.5-Coder 32B Instruct cheaper than Qwen3 VL 235B A22B Thinking?

Qwen2.5-Coder 32B Instruct is 5.0x cheaper for input tokens. Qwen2.5-Coder 32B Instruct costs $0.09/M input and $0.09/M output via lambda. Qwen3 VL 235B A22B Thinking costs $0.45/M input and $3.49/M output via deepinfra.

What are the context window sizes for Qwen2.5-Coder 32B Instruct and Qwen3 VL 235B A22B Thinking?

Qwen2.5-Coder 32B Instruct supports 128K tokens and Qwen3 VL 235B A22B Thinking supports 262K tokens. A larger context window lets you process longer documents, conversations, or codebases in a single request.

What are the main differences between Qwen2.5-Coder 32B Instruct and Qwen3 VL 235B A22B Thinking?

Key differences include context window (128K vs 262K), input pricing ($0.09 vs $0.45/M), multimodal support (no vs yes). See the full comparison above for benchmark-by-benchmark results.