Model Comparison

Qwen3-235B-A22B-Thinking-2507 vs Qwen3 VL 8B InstructWhich is better in 2026?

Qwen3-235B-A22B-Thinking-2507 significantly outperforms across most benchmarks. Qwen3 VL 8B Instruct is 5.3x cheaper per token.

Verdict: Qwen3-235B-A22B-Thinking-2507 vs Qwen3 VL 8B Instruct — which is better?

Qwen3-235B-A22B-Thinking-2507 (by Alibaba Cloud / Qwen Team) and Qwen3 VL 8B Instruct (by Alibaba Cloud / Qwen Team) are two of the AI models people compare most. Here is how they stack up on benchmarks, price and capabilities, and which one to pick in 2026.

Qwen3-235B-A22B-Thinking-2507 outperforms in 14 benchmarks (AIME 2025, BFCL-v3, HMMT25, IFEval, Include, LiveBench 20241125, LiveCodeBench v6, MMLU-Pro, MMLU-ProX, MMLU-Redux, Multi-IF, PolyMATH, SuperGPQA, WritingBench), while Qwen3 VL 8B Instruct is better at 0 benchmarks. Qwen3-235B-A22B-Thinking-2507 significantly outperforms across most benchmarks.

On price, Qwen3 VL 8B Instruct is roughly 5.3x cheaper per token on a blended 3:1 input/output basis, which adds up quickly at production volume.

Qwen3-235B-A22B-Thinking-2507 also accepts a larger context window (262,144 input tokens), making it the stronger choice for long documents and large codebases.

Choose Qwen3-235B-A22B-Thinking-2507 if…

  • you want the strongest raw capability — it leads on 14 of 14 shared benchmarks
  • you process long inputs — it offers a 262,144 token context window

Choose Qwen3 VL 8B Instruct if…

  • cost matters — it's about 5.3x cheaper per token
  • you want the most recent training data — it shipped Sep 2025

Performance Benchmarks

Comparative analysis across standard metrics

14 benchmarks

Qwen3-235B-A22B-Thinking-2507 outperforms in 14 benchmarks (AIME 2025, BFCL-v3, HMMT25, IFEval, Include, LiveBench 20241125, LiveCodeBench v6, MMLU-Pro, MMLU-ProX, MMLU-Redux, Multi-IF, PolyMATH, SuperGPQA, WritingBench), while Qwen3 VL 8B Instruct is better at 0 benchmarks.

Qwen3-235B-A22B-Thinking-2507 significantly outperforms across most benchmarks.

Tue Jun 16 2026 • llm-stats.com

Arena Performance

Human preference votes

Pricing Analysis

Price comparison per million tokens

Qwen3 VL 8B Instruct costs less

For input processing, Qwen3-235B-A22B-Thinking-2507 ($0.30/1M tokens) is 3.8x more expensive than Qwen3 VL 8B Instruct ($0.08/1M tokens).

For output processing, Qwen3-235B-A22B-Thinking-2507 ($3.00/1M tokens) is 6.0x more expensive than Qwen3 VL 8B Instruct ($0.50/1M tokens).

In conclusion, Qwen3-235B-A22B-Thinking-2507 is more expensive than Qwen3 VL 8B Instruct.*

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

Lowest available price from all providers
Tue Jun 16 2026 • llm-stats.com
Alibaba Cloud / Qwen Team
Qwen3-235B-A22B-Thinking-2507
Input tokens$0.30
Output tokens$3.00
Best providerFireworks
Alibaba Cloud / Qwen Team
Qwen3 VL 8B Instruct
Input tokens$0.08
Output tokens$0.50
Best providerNovita
Notice missing or incorrect data?Start an Issue

Model Size

Parameter count comparison

226.0B diff

Qwen3-235B-A22B-Thinking-2507 has 226.0B more parameters than Qwen3 VL 8B Instruct, making it 2511.1% larger.

Alibaba Cloud / Qwen Team
Qwen3-235B-A22B-Thinking-2507
235.0Bparameters
Alibaba Cloud / Qwen Team
Qwen3 VL 8B Instruct
9.0Bparameters
235.0B
Qwen3-235B-A22B-Thinking-2507
9.0B
Qwen3 VL 8B Instruct

Context Window

Maximum input and output token capacity

Qwen3-235B-A22B-Thinking-2507 accepts 262,144 input tokens compared to Qwen3 VL 8B Instruct's 131,072 tokens. Qwen3-235B-A22B-Thinking-2507 can generate longer responses up to 131,072 tokens, while Qwen3 VL 8B Instruct is limited to 32,768 tokens.

Alibaba Cloud / Qwen Team
Qwen3-235B-A22B-Thinking-2507
Input262,144 tokens
Output131,072 tokens
Alibaba Cloud / Qwen Team
Qwen3 VL 8B Instruct
Input131,072 tokens
Output32,768 tokens
Tue Jun 16 2026 • llm-stats.com

Input Capabilities

Supported data types and modalities

Qwen3 VL 8B Instruct supports multimodal inputs, whereas Qwen3-235B-A22B-Thinking-2507 does not.

Qwen3 VL 8B Instruct can handle both text and other forms of data like images, making it suitable for multimodal applications.

Qwen3-235B-A22B-Thinking-2507

Text
Images
Audio
Video

Qwen3 VL 8B Instruct

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.

Qwen3-235B-A22B-Thinking-2507

Apache 2.0

Open weights

Qwen3 VL 8B Instruct

Apache 2.0

Open weights

Release Timeline

When each model was launched

Qwen3-235B-A22B-Thinking-2507 was released on 2025-07-25, while Qwen3 VL 8B Instruct was released on 2025-09-22.

Qwen3 VL 8B Instruct is 2 months newer than Qwen3-235B-A22B-Thinking-2507.

Qwen3-235B-A22B-Thinking-2507

Jul 25, 2025

10 months ago

Qwen3 VL 8B Instruct

Sep 22, 2025

8 months ago

1mo 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

Qwen3-235B-A22B-Thinking-2507 is available from Fireworks, Novita. Qwen3 VL 8B Instruct is available from Novita, DeepInfra.

Qwen3-235B-A22B-Thinking-2507

fireworks logo
Fireworks
Input Price:Input: $0.30/1MOutput Price:Output: $3.00/1M
novita logo
Novita
Input Price:Input: $0.30/1MOutput Price:Output: $3.00/1M

Qwen3 VL 8B Instruct

novita logo
Novita
Input Price:Input: $0.08/1MOutput Price:Output: $0.50/1M
deepinfra logo
Deepinfra
Input Price:Input: $0.18/1MOutput Price:Output: $0.69/1M
* Prices shown are per million tokens

Outputs Comparison

Notice missing or incorrect data?Start an Issue discussion

Key Takeaways

Larger context window (262,144 tokens)
Higher AIME 2025 score (92.3% vs 45.9%)
Higher BFCL-v3 score (71.9% vs 66.3%)
Higher HMMT25 score (83.9% vs 32.5%)
Higher IFEval score (87.8% vs 83.7%)
Higher Include score (81.0% vs 67.0%)
Higher LiveBench 20241125 score (78.4% vs 62.0%)
Higher LiveCodeBench v6 score (74.1% vs 39.3%)
Higher MMLU-Pro score (84.4% vs 71.6%)
Higher MMLU-ProX score (81.0% vs 65.4%)
Higher MMLU-Redux score (93.8% vs 84.9%)
Higher Multi-IF score (80.6% vs 75.1%)
Higher PolyMATH score (60.1% vs 30.4%)
Higher SuperGPQA score (64.9% vs 44.5%)
Higher WritingBench score (88.3% vs 83.1%)
Alibaba Cloud / Qwen Team

Qwen3 VL 8B Instruct

View details

Alibaba Cloud / Qwen Team

Supports multimodal inputs
Less expensive input tokens
Less expensive output tokens

Detailed Comparison

FAQ

Common questions about Qwen3-235B-A22B-Thinking-2507 vs Qwen3 VL 8B Instruct.

Which is better, Qwen3-235B-A22B-Thinking-2507 or Qwen3 VL 8B Instruct?

Qwen3-235B-A22B-Thinking-2507 significantly outperforms across most benchmarks. Qwen3-235B-A22B-Thinking-2507 is made by Alibaba Cloud / Qwen Team and Qwen3 VL 8B Instruct 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 Qwen3-235B-A22B-Thinking-2507 compare to Qwen3 VL 8B Instruct in benchmarks?

Qwen3-235B-A22B-Thinking-2507 scores MMLU-Redux: 93.8%, AIME 2025: 92.3%, WritingBench: 88.3%, IFEval: 87.8%, Creative Writing v3: 86.1%. Qwen3 VL 8B Instruct scores DocVQAtest: 96.1%, ScreenSpot: 94.4%, OCRBench: 89.6%, AI2D: 85.7%, MMBench-V1.1: 85.0%.

Is Qwen3-235B-A22B-Thinking-2507 cheaper than Qwen3 VL 8B Instruct?

Qwen3 VL 8B Instruct is 3.8x cheaper for input tokens. Qwen3-235B-A22B-Thinking-2507 costs $0.30/M input and $3.00/M output via fireworks. Qwen3 VL 8B Instruct costs $0.08/M input and $0.50/M output via novita.

What are the context window sizes for Qwen3-235B-A22B-Thinking-2507 and Qwen3 VL 8B Instruct?

Qwen3-235B-A22B-Thinking-2507 supports 262K tokens and Qwen3 VL 8B Instruct supports 131K tokens. A larger context window lets you process longer documents, conversations, or codebases in a single request.

What are the main differences between Qwen3-235B-A22B-Thinking-2507 and Qwen3 VL 8B Instruct?

Key differences include context window (262K vs 131K), input pricing ($0.30 vs $0.08/M), multimodal support (no vs yes). See the full comparison above for benchmark-by-benchmark results.