Gemma 4 31B vs Qwen3.6 27B
How do these models stack up? Below is an expert side-by-side comparison of specifications, context window capacity, live pricing per million tokens, and standardized benchmark scores for Gemma 4 31B and Qwen3.6 27B.
Gemma 4 31B
Gemma 4 31B Instruct is Google DeepMind's 30.7B dense multimodal model supporting text and image input with text output. Features a 256K token context window, configurable thinking/reasoning mode, native function...
Qwen3.6 27B
Qwen3.6 27B is a dense 27-billion-parameter language model from the Qwen Team at Alibaba, released in April 2026. It features hybrid multimodal capabilities — accepting text, image, and video inputs...
Technical Specifications
| Specification | Gemma 4 31B | Qwen3.6 27B |
|---|---|---|
| Provider | Alibaba | |
| Context Window | 262,144 tokens | 262,144 tokens |
| Agent Suitability | N/A | N/A |
| Time to First Token (TTFT) | N/A | N/A |
| Deployment Model | managed api | self hostable |
| Production Stability | stable | stable |
| API Available | Yes | Yes |
| Released Date | 2026-04-02 | 2026-04-27 |
API Pricing Comparison
Input Price per Million Tokens
Gemma 4 31B
$0.12
Qwen3.6 27B
$0.28
Output Price per Million Tokens
Gemma 4 31B
$0.35
Qwen3.6 27B
$2.40
Want to test both models live?
Run side-by-side prompt prompts in our dynamic Sandbox. Check execution speeds, latency metrics, and compute actual costs in real-time.
Benchmark Performance Metrics
Scores show the raw performance percentages verified across key evaluation suites. Higher bars indicate superior accuracy and capability in that domain.
Gemma 4 31B Quirks & Gotchas
No developer gotchas reported.
Qwen3.6 27B Quirks & Gotchas
No developer gotchas reported.