Gemma 4 26B A4B vs Qwen3 VL 32B Instruct
Gemma 4 26B A4B
Qwen3 VL 32B Instruct
| Gemma 4 26B A4B | Qwen3 VL 32B Instruct | |
|---|---|---|
| Provider | Qwen | |
| Context window Maximum tokens (input + output) the model can process in a single request. Glossary β | 262,144 | 131,072 |
| Capabilities Optional capabilities the model advertises: vision (images), tools (function calling), json_mode (structured output). | vision, tools, json_mode | vision, tools, json_mode |
| Input $ / 1M tokens Cost for tokens you send (prompt + context). Cheaper side highlighted. Glossary β | 0.0600 | 0.1040 |
| Output $ / 1M tokens Cost for tokens the model generates. Output is normally 3β5Γ pricier than input. Glossary β | 0.3300 | 0.4160 |
Frequently asked questions
Which is cheaper, Gemma 4 26B A4B or Qwen3 VL 32B Instruct?
Gemma 4 26B A4B is cheaper than Qwen3 VL 32B Instruct on a 50/50 input/output blend by about $0.065 per 1M tokens. Exact savings depend on your input-vs-output ratio β use the cost calculator on this page for a workload-specific estimate.
Which has a larger context window, Gemma 4 26B A4B or Qwen3 VL 32B Instruct?
Gemma 4 26B A4B has the larger context window at 262k tokens versus 131k tokens for Qwen3 VL 32B Instruct. That means Gemma 4 26B A4B can ingest about 2.0x as much text per request.
What is the difference between Gemma 4 26B A4B and Qwen3 VL 32B Instruct?
Gemma 4 26B A4B comes from Google; Qwen3 VL 32B Instruct comes from Qwen. They differ in pricing, context window, and supported capabilities β see the side-by-side table on this page for the exact figures, refreshed nightly.