Gemini 2.5 Pro vs Llama 2 13B Chat
Gemini 2.5 Pro (2025) and Llama 2 13B Chat (2023) are compact production models from Google DeepMind and AI at Meta. Gemini 2.5 Pro ships a 1M-token context window, while Llama 2 13B Chat ships a 4K-token context window. On Google-Proof Q&A, Gemini 2.5 Pro leads by 44.6 pts. On pricing, Llama 2 13B Chat 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 2 13B Chat is ~1150% cheaper at $0.1/1M; pay for Gemini 2.5 Pro only for coding workflow support.
Specs
| Released | 2025-06-17 | 2023-07-18 |
| Context window | 1M | 4K |
| Parameters | — | 13B |
| Architecture | decoder only | decoder only |
| License | Proprietary | Open Source |
| Knowledge cutoff | 2025-01 | - |
Pricing and availability
| Gemini 2.5 Pro | Llama 2 13B Chat | |
|---|---|---|
| Input price | $1.25/1M tokens | $0.1/1M tokens |
| Output price | $10/1M tokens | $0.5/1M tokens |
| Providers |
Capabilities
| Gemini 2.5 Pro | Llama 2 13B Chat | |
|---|---|---|
| Vision | ||
| Multimodal | ||
| Reasoning | ||
| Function calling | ||
| Tool use | ||
| Structured outputs | ||
| Code execution |
Benchmarks
| Benchmark | Gemini 2.5 Pro | Llama 2 13B Chat |
|---|---|---|
| Google-Proof Q&A | 86.4 | 41.8 |
| HumanEval | 93.1 | 59.3 |
Deep dive
On shared benchmark coverage, Google-Proof Q&A has Gemini 2.5 Pro at 86.4 and Llama 2 13B Chat at 41.8, with Gemini 2.5 Pro ahead by 44.6 points; HumanEval has Gemini 2.5 Pro at 93.1 and Llama 2 13B Chat at 59.3, with Gemini 2.5 Pro ahead by 33.8 points. The largest visible gap is 44.6 points on Google-Proof Q&A, 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, and code execution: Gemini 2.5 Pro. 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 Pro lists $1.25/1M input and $10/1M output tokens, while Llama 2 13B Chat lists $0.1/1M input and $0.5/1M output tokens on the cheapest tracked provider. A 70/30 input-output blend puts Llama 2 13B Chat lower by about $3.66 per million blended tokens. Availability is 3 providers versus 12, so concentration risk also matters.
Choose Gemini 2.5 Pro when coding workflow support and larger context windows are central to the workload. Choose Llama 2 13B Chat 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 Pro or Llama 2 13B Chat?
Gemini 2.5 Pro supports 1M tokens, while Llama 2 13B Chat supports 4K 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 2 13B Chat?
Llama 2 13B Chat is cheaper on tracked token pricing. Gemini 2.5 Pro costs $1.25/1M input and $10/1M output tokens. Llama 2 13B Chat costs $0.1/1M input and $0.5/1M output tokens. Provider discounts or batch pricing can still change the final bill.
Is Gemini 2.5 Pro or Llama 2 13B Chat open source?
Gemini 2.5 Pro is listed under Proprietary. Llama 2 13B Chat 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 2 13B Chat?
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 2 13B Chat?
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 2 13B Chat?
Gemini 2.5 Pro is available on Google AI Studio, GCP Vertex AI, and OpenRouter. Llama 2 13B Chat is available on Alibaba Cloud PAI-EAS, AWS Bedrock, Microsoft Foundry, GCP Vertex AI, and Cloudflare Workers 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.