Compare the listed model data for Qwen3 VL 235B Thinking by Qwen and Gemma 4 318B by Google. Benchmark and pricing records are not a controlled test and may change.
Data last updated: 2026-10-16. Verify current model details with each provider.
What the listed data says
Qwen3 VL 235B Thinking: 128K tokens; Gemma 4 318B: 1M tokens. Gemma 4 318B has the larger listed context window. Qwen3 VL 235B Thinking is listed for coding, reasoning, vision, multimodal input, long-context tasks; Gemma 4 318B is listed for coding, reasoning, vision, multimodal input, long-context tasks. Shared catalog benchmark entries: DocVQA: Qwen3 VL 235B Thinking 97.2%; Gemma 4 318B 93.1%. These records are reference data, not a controlled head-to-head test; verify current pricing and specifications with each provider.
Catalog source links
Use these model and provider links to verify current specifications, pricing, and availability.
The first listed parameter quantities are 235B total (22B active via MoE) and 318B; the larger quantity is 1.35× the smaller. Total and active MoE parameters are not directly equivalent.
A release-date gap cannot be calculated from the catalog values (Qwen3 VL 235B Thinking: 2025; Gemma 4 318B: June 2025).
Cost example: 1M input and 1M output tokens
A cost example for 1M input plus 1M output tokens cannot be calculated reliably because separate numeric input and output rates are not listed for both models.
Choose Qwen3 VL 235B Thinking if…
Choose Qwen3 VL 235B Thinking when your task aligns with catalog-listed uses or strengths such as Frontier-level visual document analysis, Complex chart and scientific figure reasoning, Research requiring highest open VLM quality, World's most capable open VLM — 235B knowledge base with vision and reasoning.
Choose Gemma 4 318B if…
Choose Gemma 4 318B when your task aligns with catalog-listed uses or strengths such as Enterprise multimodal AI requiring Google-grade quality, Long-document visual analysis: PDF, charts, slides, Multilingual enterprise AI serving global markets, Google's flagship open-weight model — brings DeepMind research quality to open deployment.
Catalog specifications for Qwen3 VL 235B Thinking and Gemma 4 318B
Specification
Qwen3 VL 235B Thinking
Gemma 4 318B
Provider
Qwen
Google
Parameters
235B total (22B active via MoE)
318B
Context window
128K tokens
1M tokens
Maximum output
Not listed
Not listed
Catalog pricing
Apache 2.0 — free
Gemma Terms of Use — free for most uses
Listed input/output cost per 1M tokens
input $0.8, output $1.5 per 1M tokens
Separate numeric input/output rates not listed
License
Apache 2.0
Gemma Terms of Use
Coding support
Listed
Listed
Reasoning support
Listed
Listed
Vision input
Listed
Listed
Multimodal
Listed
Listed
Open weights
Yes
Yes
Benchmark: DocVQA
97.2%
93.1%
Figures are transcribed from LITHOVEX model records. Benchmark versions and evaluation setups may differ; pricing and specifications can change. Check each provider's current documentation before making a decision.
Frequently Asked Questions
What is different between Qwen3 VL 235B Thinking and Gemma 4 318B?
Qwen3 VL 235B Thinking: 128K tokens; Gemma 4 318B: 1M tokens. Gemma 4 318B has the larger listed context window. Qwen3 VL 235B Thinking is listed for coding, reasoning, vision, multimodal input, long-context tasks; Gemma 4 318B is listed for coding, reasoning, vision, multimodal input, long-context tasks. Shared catalog benchmark entries: DocVQA: Qwen3 VL 235B Thinking 97.2%; Gemma 4 318B 93.1%. These records are reference data, not a controlled head-to-head test; verify current pricing and specifications with each provider.
What benchmark values are listed for Qwen3 VL 235B Thinking and Gemma 4 318B?
DocVQA: Qwen3 VL 235B Thinking 97.2%; Gemma 4 318B 93.1%. The catalog values may use different versions and evaluation setups, so they are reference points rather than a controlled head-to-head result.
Which model has the larger listed context window?
Qwen3 VL 235B Thinking: 128K tokens; Gemma 4 318B: 1M tokens. Gemma 4 318B has the larger listed context window.
What are the listed costs per million tokens for Qwen3 VL 235B Thinking and Gemma 4 318B?
Qwen3 VL 235B Thinking: input $0.8, output $1.5 per 1M tokens (Apache 2.0 — free). Gemma 4 318B: Separate numeric input/output rates not listed (Gemma Terms of Use — free for most uses). Where separate numeric input and output rates are available, the worked example uses 1M input plus 1M output tokens. Confirm current terms with each provider.
How far apart are the listed release dates for Qwen3 VL 235B Thinking and Gemma 4 318B?
The catalog lists Qwen3 VL 235B Thinking as 2025 and Gemma 4 318B as June 2025; a release-date gap cannot be calculated from both records.
When was the comparison data last updated?
The model catalog records 2026-10-16 as its data update date. Provider specifications and prices may have changed since then.
How should I choose between Qwen3 VL 235B Thinking and Gemma 4 318B?
Compare the listed specifications and capabilities, review the benchmark notes, then test both with the same representative prompt for your task. This page does not claim a universal winner.
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