GPT-4.1 nano vs Qwen3.8 Flash
Qwen3.8 Flash leads the LLM Stats Score 49.6 to 1.9. GPT-4.1 nano is 1.3x cheaper per token.
OpenAI · Alibaba Cloud / Qwen Team · Updated for 2026
Which is better?
Qwen3.8 Flash leads the overall LLM Stats Score 49.6 to 1.9, ranking #16 overall.
In the 2 individual benchmarks reported for both models, Qwen3.8 Flash wins 2; this is a narrower head-to-head signal than the composite indexes.
On price, GPT-4.1 nano is roughly 1.3x cheaper per token on a blended 3:1 input/output basis, which adds up quickly at production volume.
GPT-4.1 nano also accepts a larger context window (1,047,576 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 GPT-4.1 nano
- cost matters — it's about 1.3x cheaper per token
- you process long inputs — it offers a 1,047,576 token context window
Choose Qwen3.8 Flash
- overall performance matters — it scores 49.6 and ranks #16 on LLM Stats
- your work emphasizes reasoning and coding — 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 Aug 2026
At a glance
The differences that matter most.
Capability indexes
Additional strengths measured across groups of related public benchmarks
Individual benchmarks
24 reported for GPT-4.1 nano · 22 for Qwen3.8 Flash
GPT-4.1 nano outperforms in 0 benchmarks, while Qwen3.8 Flash is better at 2 benchmarks (CharXiv-R, GPQA).
Qwen3.8 Flash 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, GPT-4.1 nano ($0.10/1M tokens) is 1.5x cheaper than Qwen3.8 Flash ($0.15/1M tokens).
For output processing, GPT-4.1 nano ($0.40/1M tokens) is 1.2x cheaper than Qwen3.8 Flash ($0.47/1M tokens).
In conclusion, Qwen3.8 Flash is more expensive than GPT-4.1 nano.*
* Using a 3:1 ratio of input to output tokens
Context Window
Maximum input and output token capacity
GPT-4.1 nano accepts 1,047,576 input tokens compared to Qwen3.8 Flash's 1,000,000 tokens. Qwen3.8 Flash can generate longer responses up to 131,072 tokens, while GPT-4.1 nano is limited to 32,768 tokens.
Input capabilities
Documented input modalities across available providers
Both GPT-4.1 nano and Qwen3.8 Flash support multimodal inputs.
They are both capable of processing various types of data, offering versatility in application.
GPT-4.1 nano
Qwen3.8 Flash
License
Usage and distribution terms
Both models are licensed under proprietary licenses.
Both models have usage restrictions defined by their respective organizations.
Proprietary
Closed source
Proprietary
Closed source
Release Timeline
When each model was launched
GPT-4.1 nano was released on 2025-04-14, while Qwen3.8 Flash was released on 2026-08-26.
Qwen3.8 Flash is 17 months newer than GPT-4.1 nano.
Apr 14, 2025
1.4 years ago
Aug 26, 2026
4 days ago
1.4yr newerKnowledge Cutoff
When training data ends
GPT-4.1 nano has a documented knowledge cutoff of 2024-05-31, while Qwen3.8 Flash's cutoff date is not specified.
We can confirm GPT-4.1 nano's training data extends to 2024-05-31, but cannot make a direct comparison without Qwen3.8 Flash's cutoff date.
May 2024
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Provider Availability
GPT-4.1 nano is available from OpenAI. Qwen3.8 Flash is available from Novita.
GPT-4.1 nano
Qwen3.8 Flash
Outputs Comparison
Judge for yourself.
Run your own prompts against GPT-4.1 nano and Qwen3.8 Flash side-by-side, then vote on the output you prefer.
FAQ
Common questions about GPT-4.1 nano vs Qwen3.8 Flash.