Gemini 2.5 Pro vs Llama 3.2 1B
Gemini 2.5 Pro (2025) and Llama 3.2 1B (2024) are compact production models from Google DeepMind and AI at Meta. Gemini 2.5 Pro ships a 1M-token context window, while Llama 3.2 1B ships a 128K-token context window. On HumanEval, Gemini 2.5 Pro leads by 65 pts. On pricing, Llama 3.2 1B costs $0.1/1M input tokens versus $1.25/1M for the alternative. This comparison covers specs, pricing, capabilities, benchmarks, provider availability, and production fit.
Llama 3.2 1B is ~1150% cheaper at $0.1/1M; pay for Gemini 2.5 Pro only for coding workflow support.
Specs
| Released | 2025-06-17 | 2024-09-25 |
| Context window | 1M | 128K |
| Parameters | — | 1.23B |
| Architecture | decoder only | decoder only |
| License | Proprietary | Open Source |
| Knowledge cutoff | 2025-01 | 2023-12 |
Pricing and availability
| Gemini 2.5 Pro | Llama 3.2 1B | |
|---|---|---|
| Input price | $1.25/1M tokens | $0.1/1M tokens |
| Output price | $10/1M tokens | $0.1/1M tokens |
| Providers |
Capabilities
| Gemini 2.5 Pro | Llama 3.2 1B | |
|---|---|---|
| Vision | ||
| Multimodal | ||
| Reasoning | ||
| Function calling | ||
| Tool use | ||
| Structured outputs | ||
| Code execution |
Benchmarks
| Benchmark | Gemini 2.5 Pro | Llama 3.2 1B |
|---|---|---|
| HumanEval | 93.1 | 28.1 |
Deep dive
On shared benchmark coverage, HumanEval has Gemini 2.5 Pro at 93.1 and Llama 3.2 1B at 28.1, with Gemini 2.5 Pro ahead by 65 points. The largest visible gap is 65 points on HumanEval, which matters most when that benchmark mirrors your workload. Treat isolated benchmark wins as directional, because provider routing, prompt style, and tool access can move real application results.
The capability footprint differs most on vision: Gemini 2.5 Pro, multimodal input: Gemini 2.5 Pro, function calling: Gemini 2.5 Pro, tool use: Gemini 2.5 Pro, structured outputs: Gemini 2.5 Pro, and code execution: Gemini 2.5 Pro. Both models share the core language-model surface, so the practical split is not just feature count. Use those differences to decide whether the page is about raw model quality, agentic coding support, multimodal ingestion, or predictable structured API behavior.
For cost, Gemini 2.5 Pro lists $1.25/1M input and $10/1M output tokens, while Llama 3.2 1B lists $0.1/1M input and $0.1/1M output tokens on the cheapest tracked provider. A 70/30 input-output blend puts Llama 3.2 1B lower by about $3.77 per million blended tokens. Availability is 3 providers versus 1, so concentration risk also matters.
Choose Gemini 2.5 Pro when coding workflow support, larger context windows, and broader provider choice are central to the workload. Choose Llama 3.2 1B when provider fit and lower input-token cost are more important. For production, rerun your own prompts through the exact provider, region, and tool stack you plan to ship.
FAQ
Which has a larger context window, Gemini 2.5 Pro or Llama 3.2 1B?
Gemini 2.5 Pro supports 1M tokens, while Llama 3.2 1B supports 128K tokens. That gap matters most for long documents, large codebases, retrieval-heavy agents, and conversations where earlier context must remain visible.
Which is cheaper, Gemini 2.5 Pro or Llama 3.2 1B?
Llama 3.2 1B is cheaper on tracked token pricing. Gemini 2.5 Pro costs $1.25/1M input and $10/1M output tokens. Llama 3.2 1B costs $0.1/1M input and $0.1/1M output tokens. Provider discounts or batch pricing can still change the final bill.
Is Gemini 2.5 Pro or Llama 3.2 1B open source?
Gemini 2.5 Pro is listed under Proprietary. Llama 3.2 1B is listed under Open Source. License labels affect whether you can self-host, redistribute weights, or rely only on hosted APIs, so confirm the upstream license before deployment.
Which is better for vision, Gemini 2.5 Pro or Llama 3.2 1B?
Gemini 2.5 Pro has the clearer documented vision signal in this comparison. If vision is mission-critical, validate it against the provider endpoint because model-level support and API-level exposure can differ.
Which is better for multimodal input, Gemini 2.5 Pro or Llama 3.2 1B?
Gemini 2.5 Pro has the clearer documented multimodal input signal in this comparison. If multimodal input is mission-critical, validate it against the provider endpoint because model-level support and API-level exposure can differ.
Where can I run Gemini 2.5 Pro and Llama 3.2 1B?
Gemini 2.5 Pro is available on Google AI Studio, GCP Vertex AI, and OpenRouter. Llama 3.2 1B is available on Fireworks AI. Provider coverage can affect latency, region availability, compliance posture, and fallback options.
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Last reviewed: 2026-04-24. Data sourced from public model cards and provider documentation.