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Gemini 1.5 Flash 8B vs Qwen3-235B-A22B-Thinking-2507

Qwen3-235B-A22B-Thinking-2507 leads the LLM Stats Score 28.1 to -0.8. Gemini 1.5 Flash 8B is 7.6x cheaper per token.

Google · Alibaba Cloud / Qwen Team · Updated for 2026

Which is better?

Qwen3-235B-A22B-Thinking-2507 leads the overall LLM Stats Score 28.1 to -0.8, ranking #134 overall.

In the 2 individual benchmarks reported for both models, Qwen3-235B-A22B-Thinking-2507 wins 2; this is a narrower head-to-head signal than the composite indexes.

On price, Gemini 1.5 Flash 8B is roughly 7.6x cheaper per token on a blended 3:1 input/output basis, which adds up quickly at production volume.

Gemini 1.5 Flash 8B also accepts a larger context window (1,048,576 input tokens), making it the stronger choice for long documents and large codebases.

Based on current LLM Stats indexes, shared benchmarks, pricing, and model metadata for 2026.

Choose Gemini 1.5 Flash 8B

  • cost matters — it's about 7.6x cheaper per token
  • you process long inputs — it offers a 1,048,576 token context window

Choose Qwen3-235B-A22B-Thinking-2507

  • overall performance matters — it scores 28.1 and ranks #134 on LLM Stats
  • your work emphasizes reasoning — it leads those capability indexes
  • you value its reported benchmark strengths — it wins 2 of 2 exact shared results
  • you want the most recent training data — it shipped Jul 2025
  • you need open weights you can self-host or fine-tune

At a glance

The differences that matter most.

Core performance indexes
-0.8
#330
28.1
#134
-0.4
#321
28.4
#127
Cost, coverage & limits
Benchmark wins
0 of 2
2 of 2
Input price
$0.07 / M
$0.30 / M
Output price
$0.30 / M
$3.00 / M
Context window
1,048,576
262,144

Capability indexes

Additional strengths measured across groups of related public benchmarks

2 shared
Index
Gemini 1.5 Flash 8B
Qwen3-235B-A22B-Thinking-2507
2.4#292
31.3#69
-2.5#190
12.1#105
Conservative TrueSkill rating · higher is betterHow scores work

Individual benchmarks

13 reported for Gemini 1.5 Flash 8B · 25 for Qwen3-235B-A22B-Thinking-2507

2 shared

Gemini 1.5 Flash 8B outperforms in 0 benchmarks, while Qwen3-235B-A22B-Thinking-2507 is better at 2 benchmarks (GPQA, MMLU-Pro).

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

Mon Sep 14 2026 • llm-stats.com

Human preference

Blind head-to-head votes and playground preference scores

Pricing Analysis

Price comparison per million tokens

Gemini 1.5 Flash 8B costs less

For input processing, Gemini 1.5 Flash 8B ($0.07/1M tokens) is 4.3x cheaper than Qwen3-235B-A22B-Thinking-2507 ($0.30/1M tokens).

For output processing, Gemini 1.5 Flash 8B ($0.30/1M tokens) is 10.0x cheaper than Qwen3-235B-A22B-Thinking-2507 ($3.00/1M tokens).

In conclusion, Qwen3-235B-A22B-Thinking-2507 is more expensive than Gemini 1.5 Flash 8B.*

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

Lowest available price from all providers
Mon Sep 14 2026 • llm-stats.com
Google
Gemini 1.5 Flash 8B
Input tokens$0.07
Output tokens$0.30
Best providerGoogle
Alibaba Cloud / Qwen Team
Qwen3-235B-A22B-Thinking-2507
Input tokens$0.30
Output tokens$3.00
Best providerFireworks
Notice missing or incorrect data?Start an Issue

Model Size

Parameter count comparison

227.0B diff

Qwen3-235B-A22B-Thinking-2507 has 227.0B more parameters than Gemini 1.5 Flash 8B, making it 2837.5% larger.

Google
Gemini 1.5 Flash 8B
8.0Bparameters
Alibaba Cloud / Qwen Team
Qwen3-235B-A22B-Thinking-2507
235.0Bparameters
8.0B
Gemini 1.5 Flash 8B
235.0B
Qwen3-235B-A22B-Thinking-2507

Context Window

Maximum input and output token capacity

Gemini 1.5 Flash 8B accepts 1,048,576 input tokens compared to Qwen3-235B-A22B-Thinking-2507's 262,144 tokens. Qwen3-235B-A22B-Thinking-2507 can generate longer responses up to 131,072 tokens, while Gemini 1.5 Flash 8B is limited to 8,192 tokens.

Google
Gemini 1.5 Flash 8B
Input1,048,576 tokens
Output8,192 tokens
Alibaba Cloud / Qwen Team
Qwen3-235B-A22B-Thinking-2507
Input262,144 tokens
Output131,072 tokens
Mon Sep 14 2026 • llm-stats.com

Input capabilities

Documented input modalities across available providers

Gemini 1.5 Flash 8B supports multimodal inputs, whereas Qwen3-235B-A22B-Thinking-2507 does not.

Gemini 1.5 Flash 8B can handle both text and other forms of data like images, making it suitable for multimodal applications.

Gemini 1.5 Flash 8B

Text
Images
Audio
Video

Qwen3-235B-A22B-Thinking-2507

Text
Images
Audio
Video

License

Usage and distribution terms

Gemini 1.5 Flash 8B is licensed under a proprietary license, while Qwen3-235B-A22B-Thinking-2507 uses Apache 2.0.

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

Gemini 1.5 Flash 8B

Proprietary

Closed source

Qwen3-235B-A22B-Thinking-2507

Apache 2.0

Open weights

Release Timeline

When each model was launched

Gemini 1.5 Flash 8B was released on 2024-03-15, while Qwen3-235B-A22B-Thinking-2507 was released on 2025-07-25.

Qwen3-235B-A22B-Thinking-2507 is 17 months newer than Gemini 1.5 Flash 8B.

Gemini 1.5 Flash 8B

Mar 15, 2024

2.5 years ago

Qwen3-235B-A22B-Thinking-2507

Jul 25, 2025

1.1 years ago

1.4yr newer

Knowledge Cutoff

When training data ends

Gemini 1.5 Flash 8B has a documented knowledge cutoff of 2024-10-01, while Qwen3-235B-A22B-Thinking-2507's cutoff date is not specified.

We can confirm Gemini 1.5 Flash 8B's training data extends to 2024-10-01, but cannot make a direct comparison without Qwen3-235B-A22B-Thinking-2507's cutoff date.

Gemini 1.5 Flash 8B

Oct 2024

Qwen3-235B-A22B-Thinking-2507

Provider Availability

Gemini 1.5 Flash 8B is available from Google. Qwen3-235B-A22B-Thinking-2507 is available from Fireworks, Novita.

Gemini 1.5 Flash 8B

google logo
Google
Input Price:Input: $0.07/1MOutput Price:Output: $0.30/1M

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
* Prices shown are per million tokens

Outputs Comparison

Notice missing or incorrect data?Start an Issue discussion

Judge for yourself.

Run your own prompts against Gemini 1.5 Flash 8B and Qwen3-235B-A22B-Thinking-2507 side-by-side, then vote on the output you prefer.

Gemini 1.5 Flash 8B
✓ Preferred
Qwen3-235B-A22B-Thinking-2507
Open in Playground

FAQ

Common questions about Gemini 1.5 Flash 8B vs Qwen3-235B-A22B-Thinking-2507.

Which is better, Gemini 1.5 Flash 8B or Qwen3-235B-A22B-Thinking-2507?

Qwen3-235B-A22B-Thinking-2507 leads the LLM Stats Score 28.1 to -0.8. Gemini 1.5 Flash 8B is made by Google and Qwen3-235B-A22B-Thinking-2507 is made by Alibaba Cloud / Qwen Team. The best choice depends on your use case — compare their capability indexes, individual benchmarks, pricing, and limits above.

How does Gemini 1.5 Flash 8B compare to Qwen3-235B-A22B-Thinking-2507 in benchmarks?

Gemini 1.5 Flash 8B scores XSTest: 92.6%, FLEURS: 86.4%, Natural2Code: 75.5%, WMT23: 72.6%, Video-MME: 66.2%. 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%.

Is Gemini 1.5 Flash 8B cheaper than Qwen3-235B-A22B-Thinking-2507?

Gemini 1.5 Flash 8B is 4.3x cheaper for input tokens. Gemini 1.5 Flash 8B costs $0.07/M input and $0.30/M output via google. Qwen3-235B-A22B-Thinking-2507 costs $0.30/M input and $3.00/M output via fireworks.

What are the context window sizes for Gemini 1.5 Flash 8B and Qwen3-235B-A22B-Thinking-2507?

Gemini 1.5 Flash 8B supports 1.0M tokens and Qwen3-235B-A22B-Thinking-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 Flash 8B and Qwen3-235B-A22B-Thinking-2507?

Key differences include LLM Stats Score (-0.8 vs 28.1), context window (1.0M vs 262K), input pricing ($0.07 vs $0.30/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 Flash 8B and Qwen3-235B-A22B-Thinking-2507?

Gemini 1.5 Flash 8B is developed by Google and Qwen3-235B-A22B-Thinking-2507 is developed by Alibaba Cloud / Qwen Team.