Gemma 3 introduces multimodality, supporting vision-language input and text outputs. It handles context windows up to 128k tokens, understands over 140 languages, and offers improved math, reasoning, and chat capabilities, including structu…
Model details →google/gemma-3-4b-it vs openai/clip-vit-base-patch32
google/gemma-3-4b-it wins on 4 of 6 axes — pricing and capability skew in its favour for most workloads.
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Model details →Side-by-side comparison
| Capability | google/gemma-3-4b-it | openai/clip-vit-base-patch32 | Winner |
|---|---|---|---|
| Context window Maximum number of input tokens the model can attend to in a single request. | 131K | Unknown | 🏆 google/gemma-3-4b-it |
| Input price (per 1M) Cost per million input tokens billed by the provider. | $0.04 | Custom | 🏆 google/gemma-3-4b-it |
| Output price (per 1M) Cost per million output tokens billed by the provider. | $0.08 | Custom | 🏆 google/gemma-3-4b-it |
| Tool / function calling First-class support for emitting structured tool calls. | — | — | Tie |
| Vision input Accepts image inputs alongside text. | Yes | — | 🏆 google/gemma-3-4b-it |
| Reasoning mode Internal chain-of-thought / extended-thinking support. | — | — | Tie |
Frequently asked questions
Is google/gemma-3-4b-it better than openai/clip-vit-base-patch32?
google/gemma-3-4b-it wins on 4 of 6 axes — pricing and capability skew in its favour for most workloads.
What's the price difference between google/gemma-3-4b-it and openai/clip-vit-base-patch32?
Input: $0.04 vs Custom per 1M tokens. Output: $0.08 vs Custom per 1M tokens.
What context windows do google/gemma-3-4b-it and openai/clip-vit-base-patch32 support?
google/gemma-3-4b-it supports up to 131K tokens. openai/clip-vit-base-patch32 supports up to Unknown tokens.
Do both google/gemma-3-4b-it and openai/clip-vit-base-patch32 support tool calling?
google/gemma-3-4b-it: not advertised. openai/clip-vit-base-patch32: not advertised.