Grok-2 vs Qwen3-235B-A22B-Thinking-2507
Qwen3-235B-A22B-Thinking-2507 leads the LLM Stats Score 28.1 to 11.5. Qwen3-235B-A22B-Thinking-2507 is 4.1x cheaper per token.
xAI · Alibaba Cloud / Qwen Team · Updated for 2026
Which is better?
Qwen3-235B-A22B-Thinking-2507 leads the overall LLM Stats Score 28.1 to 11.5, ranking #133 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, Qwen3-235B-A22B-Thinking-2507 is roughly 4.1x 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.
Based on current LLM Stats indexes, shared benchmarks, pricing, and model metadata for 2026.
Choose Grok-2
- you want predictable pricing at $2.00/M input and $10.00/M output
Choose Qwen3-235B-A22B-Thinking-2507
- overall performance matters — it scores 28.1 and ranks #133 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
- cost matters — it's about 4.1x cheaper per token
- you process long inputs — it offers a 262,144 token context window
- 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.
Capability indexes
Additional strengths measured across groups of related public benchmarks
Individual benchmarks
8 reported for Grok-2 · 25 for Qwen3-235B-A22B-Thinking-2507
Grok-2 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.
Human preference
Blind head-to-head votes and playground preference scores
Pricing Analysis
Price comparison per million tokens
For input processing, Grok-2 ($2.00/1M tokens) is 6.7x more expensive than Qwen3-235B-A22B-Thinking-2507 ($0.30/1M tokens).
For output processing, Grok-2 ($10.00/1M tokens) is 3.3x more expensive than Qwen3-235B-A22B-Thinking-2507 ($3.00/1M tokens).
In conclusion, Grok-2 is more expensive than Qwen3-235B-A22B-Thinking-2507.*
* Using a 3:1 ratio of input to output tokens
Context Window
Maximum input and output token capacity
Qwen3-235B-A22B-Thinking-2507 accepts 262,144 input tokens compared to Grok-2's 128,000 tokens. Qwen3-235B-A22B-Thinking-2507 can generate longer responses up to 131,072 tokens, while Grok-2 is limited to 8,000 tokens.
Input capabilities
Documented input modalities across available providers
Grok-2 supports multimodal inputs, whereas Qwen3-235B-A22B-Thinking-2507 does not.
Grok-2 can handle both text and other forms of data like images, making it suitable for multimodal applications.
Grok-2
Qwen3-235B-A22B-Thinking-2507
License
Usage and distribution terms
Grok-2 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.
Proprietary
Closed source
Apache 2.0
Open weights
Release Timeline
When each model was launched
Grok-2 was released on 2024-08-13, while Qwen3-235B-A22B-Thinking-2507 was released on 2025-07-25.
Qwen3-235B-A22B-Thinking-2507 is 12 months newer than Grok-2.
Aug 13, 2024
2.1 years ago
Jul 25, 2025
1.1 years ago
11mo newerKnowledge Cutoff
When training data ends
Neither model specifies a knowledge cutoff date.
Unable to compare the recency of their training data.
Provider Availability
Grok-2 is available from xAI. Qwen3-235B-A22B-Thinking-2507 is available from Fireworks, Novita.
Grok-2
Qwen3-235B-A22B-Thinking-2507
Outputs Comparison
Judge for yourself.
Run your own prompts against Grok-2 and Qwen3-235B-A22B-Thinking-2507 side-by-side, then vote on the output you prefer.
FAQ
Common questions about Grok-2 vs Qwen3-235B-A22B-Thinking-2507.