Gemini vs Llama (Groq): which should you use?
A side-by-side look at Gemini and Llama (Groq) — context window, price per million tokens, and what each one is actually better at. In Blend you can use both and switch mid-conversation.
Model data updated: 2026-08-16
Short answer
Neither wins every task. Gemini and Llama (Groq) each have questions they answer better, which is why picking one for everything costs you quality. Blend routes each question to whichever fits, so you do not have to decide up front.
- Llama 3.3 70B is the cheaper of the two on input tokens ($0.59 per 1M).
- Gemini 2.5 Pro takes the longer context window (1.0M tokens).
| Representative model | Provider | Context | Input | Output | Images |
|---|---|---|---|---|---|
| Gemini — Gemini 2.5 Pro | 1.0M | $1.25 | $10 | Yes | |
| Llama (Groq) — Llama 3.3 70B | Meta / Groq | 128K | $0.59 | $0.79 | — |
Input / Output: per 1M tokens. Prices are the providers’ list prices in USD per million tokens and can change at any time. Use them for comparison, not billing.
What Gemini is good at
Strong price-to-performance with fast responses and generous free access — the model behind Blend’s free trial.
- Excellent cost per token
- Fast responses for everyday questions
- Long context and solid multilingual support
What Llama (Groq) is good at
Open models served on Groq hardware — the fastest first-token latency available in Blend.
- Extremely fast first response
- Low cost for high volume
- Open models you can self-host elsewhere
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Related comparisons
Model capabilities and prices change often. Figures come from Blend’s automatically synced registry and are shown for comparison. All model prices