Qwen3.5 397B A17B vs Gemini Computer Use
At a Glance
| Compare | Gemini Computer UseGoogle DeepMind | |
|---|---|---|
| Pricing and Limits | ||
| Input priceFrom · USD / 1M tokens | $0.45Deepinfra ↗ · Sep 22, 2026 | $1.25Google AI ↗ · Aug 29, 2026 |
| Output priceFrom · USD / 1M tokens | $3.00Deepinfra ↗ · Sep 22, 2026 | $10.00Google AI ↗ · Aug 29, 2026 |
| Context windowMaximum documented tokens | 262K | 128K |
| Model facts checked | Aug 28, 2026View model evidence → | Aug 29, 2026View model evidence → |
Token prices are the lowest available sourced USD rates; input and output may use different providers. Cost ranking estimates output spend on LiveBench, not a full request bill. Ranking methodology →
Available Benchmarks
Side-by-Side Facts
| Field | Qwen3.5-397B-A17B | Gemini Computer Use |
|---|---|---|
| Developer | Qwen | Google DeepMind |
| Family | Qwen3 5 397b A17b | Gemini Tools |
| Model | Qwen3.5-397B-A17B | Gemini Computer Use |
| Version | Qwen3.5-397B-A17B | Gemini Computer Use |
| Lifecycle | active | preview |
| Released | 2026-02-15 | Unknown |
| Knowledge cutoff | Unknown | Unknown |
| Input modalities | Text, Image | Text, Image |
| Output modalities | Text | Text |
| Context window | 262K | 128K |
| Total parameters | 403.4B | Unknown |
| Active parameters | 17B | Unknown |
| License | apache-2.0 | Unknown |
| Open weights | Yes | No |
| API available | Yes | Yes |
| Self-hostable | Yes | No |
| Provider access | Deepinfra (Standard), Hugging Face (Standard), Openrouter (Standard), Together Ai (Standard) | Google AI (Standard), Google Gemini (Standard) |
| Capabilities | chat, generation, reasoning, tools | generation, reasoning, tools |
Qwen3.5 397B A17B Capabilities
Gemini Computer Use Capabilities
Primary Evidence
Sources and Freshness
Questions
Qwen3.5 397B A17B vs Gemini Computer Use FAQs
Is Qwen3.5 397B A17B or Gemini Computer Use better for coding?+
This comparison does not currently contain a protocol-matched coding benchmark for both Qwen3.5 397B A17B and Gemini Computer Use, so Model Markets cannot name a coding leader from pricing, context size, or capability labels alone.
Which is cheaper, Qwen3.5 397B A17B or Gemini Computer Use?+
Qwen3.5 397B A17B is $0.45 and Gemini Computer Use is $1.25 per million tokens, so Qwen3.5 397B A17B is cheaper on this metric. Qwen3.5 397B A17B is $3.00 and Gemini Computer Use is $10.00 per million tokens, so Qwen3.5 397B A17B is cheaper on this metric.
Which has a larger context window, Qwen3.5 397B A17B or Gemini Computer Use?+
Qwen3.5 397B A17B has the larger sourced context window. Qwen3.5 397B A17B supports 262K and Gemini Computer Use supports 128K.
Which performs better in benchmarks, Qwen3.5 397B A17B or Gemini Computer Use?+
There is no overall benchmark winner: At least two independently verified, protocol-matched benchmarks are required for an overall winner.
Can Qwen3.5 397B A17B or Gemini Computer Use be self-hosted?+
Qwen3.5 397B A17B is the only model in this pair currently marked as self-hostable. Qwen3.5 397B A17B is open weight; Gemini Computer Use is not marked open weight.
Can Qwen3.5 397B A17B and Gemini Computer Use understand images?+
Qwen3.5 397B A17B is documented with image input; Gemini Computer Use is documented with image input. This reflects supported input modalities, not vision quality.
Which can generate longer answers, Qwen3.5 397B A17B or Gemini Computer Use?+
Neither has a larger sourced maximum output. Qwen3.5 397B A17B is — and Gemini Computer Use is 64K.
Do Qwen3.5 397B A17B and Gemini Computer Use support reasoning and tool use?+
Qwen3.5 397B A17B: reasoning, tool calling, and image input. Gemini Computer Use: reasoning, tool calling, and image input. Feature support does not establish relative quality.
Which is available from more inference providers, Qwen3.5 397B A17B or Gemini Computer Use?+
Qwen3.5 397B A17B has 4 sourced provider routes; Gemini Computer Use has 2, so Qwen3.5 397B A17B has broader tracked availability.
Which offers better value, Qwen3.5 397B A17B or Gemini Computer Use?+
There is no universal value winner. Compare the input and output prices above with the matched benchmark result for your workload: cheaper tokens can be offset by different quality, token usage, latency, or provider availability.