Gemma 4 31B vs Qwen3.8 Flash
Qwen3.8 Flash leads the LLM Stats Score 49.5 to 33.4. Gemma 4 31B is 1.2x cheaper per token.
Google · Alibaba Cloud / Qwen Team · Updated for 2026
Which is better?
Qwen3.8 Flash leads the overall LLM Stats Score 49.5 to 33.4, ranking #18 overall.
In the 4 individual benchmarks reported for both models, Qwen3.8 Flash wins 4; this is a narrower head-to-head signal than the composite indexes.
On price, Gemma 4 31B is roughly 1.2x cheaper per token on a blended 3:1 input/output basis, which adds up quickly at production volume.
Qwen3.8 Flash also accepts a larger context window (1,000,000 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 Gemma 4 31B
- cost matters — it's about 1.2x cheaper per token
- you need open weights you can self-host or fine-tune
Choose Qwen3.8 Flash
- overall performance matters — it scores 49.5 and ranks #18 on LLM Stats
- your work emphasizes reasoning and agents — it leads those capability indexes
- you value its reported benchmark strengths — it wins 4 of 4 exact shared results
- you process long inputs — it offers a 1,000,000 token context window
- 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
12 reported for Gemma 4 31B · 22 for Qwen3.8 Flash
Gemma 4 31B outperforms in 0 benchmarks, while Qwen3.8 Flash is better at 4 benchmarks (GPQA, Humanity's Last Exam, LiveCodeBench v6, MathVision).
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, Gemma 4 31B ($0.13/1M tokens) is 1.2x cheaper than Qwen3.8 Flash ($0.15/1M tokens).
For output processing, Gemma 4 31B ($0.38/1M tokens) is 1.2x cheaper than Qwen3.8 Flash ($0.47/1M tokens).
In conclusion, Qwen3.8 Flash is more expensive than Gemma 4 31B.*
* Using a 3:1 ratio of input to output tokens
Model Size
Parameter count comparison
Qwen3.8 Flash has 94.3B more parameters than Gemma 4 31B, making it 307.2% larger.
Context Window
Maximum input and output token capacity
Qwen3.8 Flash accepts 1,000,000 input tokens compared to Gemma 4 31B's 262,144 tokens. Both models can generate responses up to 131,072 tokens.
Input capabilities
Documented input modalities across available providers
Both Gemma 4 31B and Qwen3.8 Flash support multimodal inputs.
They are both capable of processing various types of data, offering versatility in application.
Gemma 4 31B
Qwen3.8 Flash
License
Usage and distribution terms
Gemma 4 31B is licensed under Apache 2.0, while Qwen3.8 Flash uses a proprietary license.
License differences may affect how you can use these models in commercial or open-source projects.
Apache 2.0
Open weights
Proprietary
Closed source
Release Timeline
When each model was launched
Gemma 4 31B was released on 2026-04-02, while Qwen3.8 Flash was released on 2026-08-26.
Qwen3.8 Flash is 5 months newer than Gemma 4 31B.
Apr 2, 2026
5 months ago
Aug 26, 2026
1 weeks ago
4mo newerKnowledge Cutoff
When training data ends
Gemma 4 31B has a documented knowledge cutoff of 2025-01-01, while Qwen3.8 Flash's cutoff date is not specified.
We can confirm Gemma 4 31B's training data extends to 2025-01-01, but cannot make a direct comparison without Qwen3.8 Flash's cutoff date.
Jan 2025
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Provider Availability
Gemma 4 31B is available from DeepInfra, FriendliAI, Novita, Together. Qwen3.8 Flash is available from Novita.
Gemma 4 31B
Qwen3.8 Flash
Outputs Comparison
Judge for yourself.
Run your own prompts against Gemma 4 31B and Qwen3.8 Flash side-by-side, then vote on the output you prefer.
FAQ
Common questions about Gemma 4 31B vs Qwen3.8 Flash.