Claude 3.7 Sonnet vs Qwen3 14B
Claude 3.7 Sonnet leads the LLM Stats Score 24.0 to 18.2. Qwen3 14B is 40.0x cheaper per token.
Anthropic · Alibaba Cloud / Qwen Team · Updated for 2026
Which is better?
Claude 3.7 Sonnet leads the overall LLM Stats Score 24.0 to 18.2, ranking #167 overall.
The models split the 4 individual benchmarks reported for both models evenly.
On price, Qwen3 14B is roughly 40.0x cheaper per token on a blended 3:1 input/output basis, which adds up quickly at production volume.
Claude 3.7 Sonnet also accepts a larger context window (200,000 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 Claude 3.7 Sonnet
- overall performance matters — it scores 24.0 and ranks #167 on LLM Stats
- you process long inputs — it offers a 200,000 token context window
Choose Qwen3 14B
- cost matters — it's about 40.0x cheaper per token
- you want the most recent training data — it shipped Apr 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
11 reported for Claude 3.7 Sonnet · 17 for Qwen3 14B
Claude 3.7 Sonnet outperforms in 2 benchmarks (AIME 2024, IFEval), while Qwen3 14B is better at 2 benchmarks (AIME 2025, MATH-500).
Both models are evenly matched across the benchmarks.
Human preference
Blind head-to-head votes and playground preference scores
Pricing Analysis
Price comparison per million tokens
For input processing, Claude 3.7 Sonnet ($3.00/1M tokens) is 25.0x more expensive than Qwen3 14B ($0.12/1M tokens).
For output processing, Claude 3.7 Sonnet ($15.00/1M tokens) is 62.5x more expensive than Qwen3 14B ($0.24/1M tokens).
In conclusion, Claude 3.7 Sonnet is more expensive than Qwen3 14B.*
* Using a 3:1 ratio of input to output tokens
Context Window
Maximum input and output token capacity
Claude 3.7 Sonnet accepts 200,000 input tokens compared to Qwen3 14B's 40,960 tokens. Claude 3.7 Sonnet can generate longer responses up to 128,000 tokens, while Qwen3 14B is limited to 40,960 tokens.
Input capabilities
Documented input modalities across available providers
Claude 3.7 Sonnet supports multimodal inputs, whereas Qwen3 14B does not.
Claude 3.7 Sonnet can handle both text and other forms of data like images, making it suitable for multimodal applications.
Claude 3.7 Sonnet
Qwen3 14B
License
Usage and distribution terms
Claude 3.7 Sonnet is licensed under a proprietary license, while Qwen3 14B 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
Claude 3.7 Sonnet was released on 2025-02-24, while Qwen3 14B was released on 2025-04-28.
Qwen3 14B is 2 months newer than Claude 3.7 Sonnet.
Feb 24, 2025
1.5 years ago
Apr 28, 2025
1.4 years ago
2mo newerKnowledge Cutoff
When training data ends
Neither model specifies a knowledge cutoff date.
Unable to compare the recency of their training data.
Provider Availability
Claude 3.7 Sonnet is available from Anthropic, Bedrock, Google. Qwen3 14B is available from DeepInfra.
Claude 3.7 Sonnet
Qwen3 14B
Outputs Comparison
Judge for yourself.
Run your own prompts against Claude 3.7 Sonnet and Qwen3 14B side-by-side, then vote on the output you prefer.
FAQ
Common questions about Claude 3.7 Sonnet vs Qwen3 14B.