Model Comparison

Gemini 1.5 Pro vs Qwen3-235B-A22B-Instruct-2507Which is better in 2026?

Qwen3-235B-A22B-Instruct-2507 significantly outperforms across most benchmarks. Qwen3-235B-A22B-Instruct-2507 is 14.0x cheaper per token.

Verdict: Gemini 1.5 Pro vs Qwen3-235B-A22B-Instruct-2507 — which is better?

Gemini 1.5 Pro (by Google) and Qwen3-235B-A22B-Instruct-2507 (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.

Gemini 1.5 Pro outperforms in 0 benchmarks, while Qwen3-235B-A22B-Instruct-2507 is better at 2 benchmarks (GPQA, MMLU-Pro). Qwen3-235B-A22B-Instruct-2507 significantly outperforms across most benchmarks.

On price, Qwen3-235B-A22B-Instruct-2507 is roughly 14.0x cheaper per token on a blended 3:1 input/output basis, which adds up quickly at production volume.

Gemini 1.5 Pro also accepts a larger context window (2,097,152 input tokens), making it the stronger choice for long documents and large codebases.

Choose Gemini 1.5 Pro if…

  • you process long inputs — it offers a 2,097,152 token context window

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

  • you want the strongest raw capability — it leads on 2 of 2 shared benchmarks
  • cost matters — it's about 14.0x cheaper per token
  • you want the most recent training data — it shipped Jul 2025
  • you need open weights you can self-host or fine-tune
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Performance Benchmarks

Comparative analysis across standard metrics

2 benchmarks

Gemini 1.5 Pro outperforms in 0 benchmarks, while Qwen3-235B-A22B-Instruct-2507 is better at 2 benchmarks (GPQA, MMLU-Pro).

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

Wed Jun 24 2026 • llm-stats.com

Arena Performance

Human preference votes

Pricing Analysis

Price comparison per million tokens

Qwen3-235B-A22B-Instruct-2507 costs less

For input processing, Gemini 1.5 Pro ($2.50/1M tokens) is 16.7x more expensive than Qwen3-235B-A22B-Instruct-2507 ($0.15/1M tokens).

For output processing, Gemini 1.5 Pro ($10.00/1M tokens) is 12.5x more expensive than Qwen3-235B-A22B-Instruct-2507 ($0.80/1M tokens).

In conclusion, Gemini 1.5 Pro is more expensive than Qwen3-235B-A22B-Instruct-2507.*

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

Lowest available price from all providers
Wed Jun 24 2026 • llm-stats.com
Google
Gemini 1.5 Pro
Input tokens$2.50
Output tokens$10.00
Best providerGoogle
Alibaba Cloud / Qwen Team
Qwen3-235B-A22B-Instruct-2507
Input tokens$0.15
Output tokens$0.80
Best providerFireworks
Notice missing or incorrect data?Start an Issue→

Context Window

Maximum input and output token capacity

Gemini 1.5 Pro accepts 2,097,152 input tokens compared to Qwen3-235B-A22B-Instruct-2507's 262,144 tokens. Qwen3-235B-A22B-Instruct-2507 can generate longer responses up to 131,072 tokens, while Gemini 1.5 Pro is limited to 8,192 tokens.

Google
Gemini 1.5 Pro
Input2,097,152 tokens
Output8,192 tokens
Alibaba Cloud / Qwen Team
Qwen3-235B-A22B-Instruct-2507
Input262,144 tokens
Output131,072 tokens
Wed Jun 24 2026 • llm-stats.com

Input Capabilities

Supported data types and modalities

Gemini 1.5 Pro supports multimodal inputs, whereas Qwen3-235B-A22B-Instruct-2507 does not.

Gemini 1.5 Pro can handle both text and other forms of data like images, making it suitable for multimodal applications.

Gemini 1.5 Pro

Text
Images
Audio
Video

Qwen3-235B-A22B-Instruct-2507

Text
Images
Audio
Video

License

Usage and distribution terms

Gemini 1.5 Pro is licensed under a proprietary license, while Qwen3-235B-A22B-Instruct-2507 uses Apache 2.0.

License differences may affect how you can use these models in commercial or open-source projects.

Gemini 1.5 Pro

Proprietary

Closed source

Qwen3-235B-A22B-Instruct-2507

Apache 2.0

Open weights

Release Timeline

When each model was launched

Gemini 1.5 Pro was released on 2024-05-01, while Qwen3-235B-A22B-Instruct-2507 was released on 2025-07-22.

Qwen3-235B-A22B-Instruct-2507 is 15 months newer than Gemini 1.5 Pro.

Gemini 1.5 Pro

May 1, 2024

2.1 years ago

Qwen3-235B-A22B-Instruct-2507

Jul 22, 2025

11 months ago

1.2yr newer

Knowledge Cutoff

When training data ends

Gemini 1.5 Pro has a documented knowledge cutoff of 2023-11-01, while Qwen3-235B-A22B-Instruct-2507's cutoff date is not specified.

We can confirm Gemini 1.5 Pro's training data extends to 2023-11-01, but cannot make a direct comparison without Qwen3-235B-A22B-Instruct-2507's cutoff date.

Gemini 1.5 Pro

Nov 2023

Qwen3-235B-A22B-Instruct-2507

—

Provider Availability

Gemini 1.5 Pro is available from Google. Qwen3-235B-A22B-Instruct-2507 is available from Fireworks, Novita.

Gemini 1.5 Pro

google logo
Google
Input Price:Input: $2.50/1MOutput Price:Output: $10.00/1M

Qwen3-235B-A22B-Instruct-2507

fireworks logo
Fireworks
Input Price:Input: $0.15/1MOutput Price:Output: $0.80/1M
novita logo
Novita
Input Price:Input: $0.15/1MOutput Price:Output: $0.80/1M
* Prices shown are per million tokens

Outputs Comparison

Notice missing or incorrect data?Start an Issue discussion→

Key Takeaways

Google
Larger context window (2,097,152 tokens)
Supports multimodal inputs
Alibaba Cloud / Qwen Team
Less expensive input tokens
Less expensive output tokens
Has open weights
Higher GPQA score (77.5% vs 59.1%)
Higher MMLU-Pro score (83.0% vs 75.8%)

Detailed Comparison

AI Model Comparison Table
Feature
Google
Gemini 1.5 Pro
Alibaba Cloud / Qwen Team
Qwen3-235B-A22B-Instruct-2507

FAQ

Common questions about Gemini 1.5 Pro vs Qwen3-235B-A22B-Instruct-2507.

Which is better, Gemini 1.5 Pro or Qwen3-235B-A22B-Instruct-2507?

Qwen3-235B-A22B-Instruct-2507 significantly outperforms across most benchmarks. Gemini 1.5 Pro is made by Google and Qwen3-235B-A22B-Instruct-2507 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 Gemini 1.5 Pro compare to Qwen3-235B-A22B-Instruct-2507 in benchmarks?

Gemini 1.5 Pro scores XSTest: 98.8%, FLEURS: 93.3%, HellaSwag: 93.3%, GSM8k: 90.8%, BIG-Bench Hard: 89.2%. Qwen3-235B-A22B-Instruct-2507 scores ZebraLogic: 95.0%, MMLU-Redux: 93.1%, IFEval: 88.7%, MultiPL-E: 87.9%, Creative Writing v3: 87.5%.

Is Gemini 1.5 Pro cheaper than Qwen3-235B-A22B-Instruct-2507?

Qwen3-235B-A22B-Instruct-2507 is 16.7x cheaper for input tokens. Gemini 1.5 Pro costs $2.50/M input and $10.00/M output via google. Qwen3-235B-A22B-Instruct-2507 costs $0.15/M input and $0.80/M output via fireworks.

What are the context window sizes for Gemini 1.5 Pro and Qwen3-235B-A22B-Instruct-2507?

Gemini 1.5 Pro supports 2.1M tokens and Qwen3-235B-A22B-Instruct-2507 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 Gemini 1.5 Pro and Qwen3-235B-A22B-Instruct-2507?

Key differences include context window (2.1M vs 262K), input pricing ($2.50 vs $0.15/M), multimodal support (yes vs no), licensing (Proprietary vs Apache 2.0). See the full comparison above for benchmark-by-benchmark results.

Who makes Gemini 1.5 Pro and Qwen3-235B-A22B-Instruct-2507?

Gemini 1.5 Pro is developed by Google and Qwen3-235B-A22B-Instruct-2507 is developed by Alibaba Cloud / Qwen Team.

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