LLM ReferenceLLM Reference

Gemini 2.5 Flash Lite vs Llama 3.2 1B Instruct

Gemini 2.5 Flash Lite (2025) and Llama 3.2 1B Instruct (2024) are compact production models from Google DeepMind and AI at Meta. Gemini 2.5 Flash Lite ships a 1M-token context window, while Llama 3.2 1B Instruct ships a 128K-token context window. On pricing, Llama 3.2 1B Instruct costs $0.03/1M input tokens versus $0.1/1M for the alternative. This comparison covers specs, pricing, capabilities, benchmarks, provider availability, and production fit.

Llama 3.2 1B Instruct is ~270% cheaper at $0.03/1M; pay for Gemini 2.5 Flash Lite only for coding workflow support.

Specs

Released2025-07-222024-09-25
Context window1M128K
Parameters1.23B
Architecturedecoder onlydecoder only
LicenseProprietaryOpen Source
Knowledge cutoff2025-012023-12

Pricing and availability

Gemini 2.5 Flash LiteLlama 3.2 1B Instruct
Input price$0.1/1M tokens$0.03/1M tokens
Output price$0.4/1M tokens$0.2/1M tokens
Providers

Capabilities

Gemini 2.5 Flash LiteLlama 3.2 1B Instruct
Vision
Multimodal
Reasoning
Function calling
Tool use
Structured outputs
Code execution

Benchmarks

No shared benchmark rows are currently sourced for this pair.

Deep dive

The capability footprint differs most on vision: Gemini 2.5 Flash Lite, multimodal input: Gemini 2.5 Flash Lite, function calling: Gemini 2.5 Flash Lite, tool use: Gemini 2.5 Flash Lite, and code execution: Gemini 2.5 Flash Lite. Both models share structured outputs, 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 Flash Lite lists $0.1/1M input and $0.4/1M output tokens, while Llama 3.2 1B Instruct lists $0.03/1M input and $0.2/1M output tokens on the cheapest tracked provider. A 70/30 input-output blend puts Llama 3.2 1B Instruct lower by about $0.11 per million blended tokens. Availability is 3 providers versus 5, so concentration risk also matters.

Choose Gemini 2.5 Flash Lite when coding workflow support and larger context windows are central to the workload. Choose Llama 3.2 1B Instruct when provider fit, lower input-token cost, and broader provider choice 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 Flash Lite or Llama 3.2 1B Instruct?

Gemini 2.5 Flash Lite supports 1M tokens, while Llama 3.2 1B Instruct 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 Flash Lite or Llama 3.2 1B Instruct?

Llama 3.2 1B Instruct is cheaper on tracked token pricing. Gemini 2.5 Flash Lite costs $0.1/1M input and $0.4/1M output tokens. Llama 3.2 1B Instruct costs $0.03/1M input and $0.2/1M output tokens. Provider discounts or batch pricing can still change the final bill.

Is Gemini 2.5 Flash Lite or Llama 3.2 1B Instruct open source?

Gemini 2.5 Flash Lite is listed under Proprietary. Llama 3.2 1B Instruct 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 Flash Lite or Llama 3.2 1B Instruct?

Gemini 2.5 Flash Lite 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 Flash Lite or Llama 3.2 1B Instruct?

Gemini 2.5 Flash Lite 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 Flash Lite and Llama 3.2 1B Instruct?

Gemini 2.5 Flash Lite is available on Google AI Studio, GCP Vertex AI, and OpenRouter. Llama 3.2 1B Instruct is available on OpenRouter, Fireworks AI, NVIDIA NIM, Bitdeer AI, and AWS Bedrock. Provider coverage can affect latency, region availability, compliance posture, and fallback options.

Continue comparing

Last reviewed: 2026-04-24. Data sourced from public model cards and provider documentation.