Gemini 2.5 Pro vs Llama 3.3 70B Instruct
Gemini 2.5 Pro (2025) and Llama 3.3 70B Instruct (2025) are compact production models from Google DeepMind and AI at Meta. Gemini 2.5 Pro ships a 1M-token context window, while Llama 3.3 70B Instruct ships a 128k-token context window. On pricing, Llama 3.3 70B Instruct costs $0.96/1M input tokens versus $1.25/1M for the alternative. This comparison covers specs, pricing, capabilities, benchmarks, provider availability, and production fit.
Gemini 2.5 Pro fits 8x more tokens; pick it for long-context work and Llama 3.3 70B Instruct for tighter calls.
Decision scorecard
Local evidence first| Signal | Gemini 2.5 Pro | Llama 3.3 70B Instruct |
|---|---|---|
| Decision fit | Coding, RAG, and Agents | RAG, Long context, and Classification |
| Context window | 1M | 128k |
| Cheapest output | $10/1M tokens | $1.28/1M tokens |
| Provider routes | 3 tracked | 1 tracked |
| Shared benchmarks | 0 rows | 0 rows |
Decision tradeoffs
- Gemini 2.5 Pro has the larger context window for long prompts, retrieval packs, or transcript analysis.
- Gemini 2.5 Pro has broader tracked provider coverage for fallback and procurement flexibility.
- Gemini 2.5 Pro uniquely exposes Vision, Multimodal, and Function calling in local model data.
- Local decision data tags Gemini 2.5 Pro for Coding, RAG, and Agents.
- Llama 3.3 70B Instruct has the lower cheapest tracked output price at $1.28/1M tokens.
- Local decision data tags Llama 3.3 70B Instruct for RAG, Long context, and Classification.
Monthly cost at traffic
Estimate token spend from the cheapest tracked input and output prices on this page.
Gemini 2.5 Pro
$3,500
Cheapest tracked route: Google AI Studio
Llama 3.3 70B Instruct
$1,088
Cheapest tracked route: AWS Bedrock
Estimated monthly gap: $2,412. Batch, cache, and negotiated pricing are excluded from this local estimate.
Switch friction
- No overlapping tracked provider route is sourced for Gemini 2.5 Pro and Llama 3.3 70B Instruct; plan for SDK, billing, or endpoint changes.
- Llama 3.3 70B Instruct is $8.72/1M tokens lower on cheapest tracked output pricing before cache, batch, or negotiated discounts.
- Check replacement coverage for Vision, Multimodal, and Function calling before moving production traffic.
- No overlapping tracked provider route is sourced for Llama 3.3 70B Instruct and Gemini 2.5 Pro; plan for SDK, billing, or endpoint changes.
- Gemini 2.5 Pro is $8.72/1M tokens higher on cheapest tracked output pricing, so quality gains need to justify the spend.
- Gemini 2.5 Pro adds Vision, Multimodal, and Function calling in local capability data.
Specs
| Specification | ||
|---|---|---|
| Released | 2025-06-17 | 2025-09-01 |
| Context window | 1M | 128k |
| Parameters | — | 70 |
| Architecture | decoder only | - |
| License | Proprietary | Open Source |
| Knowledge cutoff | 2025-01 | 2023-12 |
Pricing and availability
| Pricing attribute | Gemini 2.5 Pro | Llama 3.3 70B Instruct |
|---|---|---|
| Input price | $1.25/1M tokens | $0.96/1M tokens |
| Output price | $10/1M tokens | $1.28/1M tokens |
| Providers |
Capabilities
| Capability | Gemini 2.5 Pro | Llama 3.3 70B Instruct |
|---|---|---|
| Vision | Yes | No |
| Multimodal | Yes | No |
| Reasoning | No | No |
| Function calling | Yes | No |
| Tool use | Yes | No |
| Structured outputs | Yes | Yes |
| Code execution | Yes | No |
Benchmarks
No shared benchmark rows are currently sourced for this pair.
Deep dive
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 3.3 70B Instruct lists $0.96/1M input and $1.28/1M output tokens on the cheapest tracked provider. A 70/30 input-output blend puts Llama 3.3 70B Instruct lower by about $2.82 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 3.3 70B Instruct 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. This keeps the decision grounded in measurable tradeoffs instead of brand-level assumptions.
FAQ
Which has a larger context window, Gemini 2.5 Pro or Llama 3.3 70B Instruct?
Gemini 2.5 Pro supports 1M tokens, while Llama 3.3 70B 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 Pro or Llama 3.3 70B Instruct?
Llama 3.3 70B Instruct is cheaper on tracked token pricing. Gemini 2.5 Pro costs $1.25/1M input and $10/1M output tokens. Llama 3.3 70B Instruct costs $0.96/1M input and $1.28/1M output tokens. Provider discounts or batch pricing can still change the final bill.
Is Gemini 2.5 Pro or Llama 3.3 70B Instruct open source?
Gemini 2.5 Pro is listed under Proprietary. Llama 3.3 70B 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 Pro or Llama 3.3 70B Instruct?
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 3.3 70B Instruct?
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 3.3 70B Instruct?
Gemini 2.5 Pro is available on Google AI Studio, GCP Vertex AI, and OpenRouter. Llama 3.3 70B Instruct is available on AWS Bedrock. Provider coverage can affect latency, region availability, compliance posture, and fallback options.
Continue comparing
Last reviewed: 2026-05-19. Data sourced from public model cards and provider documentation.