Gemini 2.5 Pro vs Llama 3.3 70B
Gemini 2.5 Pro (2025) and Llama 3.3 70B (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 ships a 8K-token context window. On MMLU PRO, Gemini 2.5 Pro leads by 14.9 pts. On pricing, Llama 3.3 70B costs $0.9/1M 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 125x more tokens; pick it for long-context work and Llama 3.3 70B for tighter calls.
Decision scorecard
Local evidence first| Signal | Gemini 2.5 Pro | Llama 3.3 70B |
|---|---|---|
| Decision fit | Coding, RAG, and Agents | Agents, Vision, and Classification |
| Context window | 1M | 8K |
| Cheapest output | $10/1M tokens | $0.9/1M tokens |
| Provider routes | 3 tracked | 1 tracked |
| Shared benchmarks | MMLU PRO leader | 1 rows |
Decision tradeoffs
- Gemini 2.5 Pro leads the largest shared benchmark signal on MMLU PRO by 14.9 points.
- 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 Structured outputs and Code execution in local model data.
- Local decision data tags Gemini 2.5 Pro for Coding, RAG, and Agents.
- Llama 3.3 70B has the lower cheapest tracked output price at $0.9/1M tokens.
- Local decision data tags Llama 3.3 70B for Agents, Vision, 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
$945
Cheapest tracked route: Fireworks AI
Estimated monthly gap: $2,555. 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; plan for SDK, billing, or endpoint changes.
- Llama 3.3 70B is $9.1/1M tokens lower on cheapest tracked output pricing before cache, batch, or negotiated discounts.
- Check replacement coverage for Structured outputs and Code execution before moving production traffic.
- No overlapping tracked provider route is sourced for Llama 3.3 70B and Gemini 2.5 Pro; plan for SDK, billing, or endpoint changes.
- Gemini 2.5 Pro is $9.1/1M tokens higher on cheapest tracked output pricing, so quality gains need to justify the spend.
- Gemini 2.5 Pro adds Structured outputs and Code execution in local capability data.
Specs
| Specification | ||
|---|---|---|
| Released | 2025-06-17 | 2025-12-09 |
| Context window | 1M | 8K |
| Parameters | — | 70B |
| Architecture | decoder only | decoder only |
| License | Proprietary | True |
| Knowledge cutoff | 2025-01 | 2024-12 |
Pricing and availability
| Pricing attribute | Gemini 2.5 Pro | Llama 3.3 70B |
|---|---|---|
| Input price | $1.25/1M tokens | $0.9/1M tokens |
| Output price | $10/1M tokens | $0.9/1M tokens |
| Providers |
Capabilities
| Capability | Gemini 2.5 Pro | Llama 3.3 70B |
|---|---|---|
| Vision | Yes | Yes |
| Multimodal | Yes | Yes |
| Reasoning | No | No |
| Function calling | Yes | Yes |
| Tool use | Yes | Yes |
| Structured outputs | Yes | No |
| Code execution | Yes | No |
Benchmarks
| Benchmark | Gemini 2.5 Pro | Llama 3.3 70B |
|---|---|---|
| MMLU PRO | 86.2 | 71.3 |
Deep dive
On shared benchmark coverage, MMLU PRO has Gemini 2.5 Pro at 86.2 and Llama 3.3 70B at 71.3, with Gemini 2.5 Pro ahead by 14.9 points. The largest visible gap is 14.9 points on MMLU PRO, 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 structured outputs: Gemini 2.5 Pro and code execution: Gemini 2.5 Pro. Both models share vision, multimodal input, function calling, and tool use, 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 lists $0.9/1M input and $0.9/1M output tokens on the cheapest tracked provider. A 70/30 input-output blend puts Llama 3.3 70B lower by about $2.98 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 when vision-heavy evaluation 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 3.3 70B?
Gemini 2.5 Pro supports 1M tokens, while Llama 3.3 70B supports 8K 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?
Llama 3.3 70B is cheaper on tracked token pricing. Gemini 2.5 Pro costs $1.25/1M input and $10/1M output tokens. Llama 3.3 70B costs $0.9/1M input and $0.9/1M output tokens. Provider discounts or batch pricing can still change the final bill.
Is Gemini 2.5 Pro or Llama 3.3 70B open source?
Gemini 2.5 Pro is listed under Proprietary. Llama 3.3 70B is listed under True. 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?
Both Gemini 2.5 Pro and Llama 3.3 70B expose vision. The better choice depends on benchmark fit, context budget, pricing, and whether your provider route exposes the same capability surface.
Which is better for multimodal input, Gemini 2.5 Pro or Llama 3.3 70B?
Both Gemini 2.5 Pro and Llama 3.3 70B expose multimodal input. The better choice depends on benchmark fit, context budget, pricing, and whether your provider route exposes the same capability surface.
Where can I run Gemini 2.5 Pro and Llama 3.3 70B?
Gemini 2.5 Pro is available on Google AI Studio, GCP Vertex AI, and OpenRouter. Llama 3.3 70B is available on Fireworks AI. Provider coverage can affect latency, region availability, compliance posture, and fallback options.
Continue comparing
Last reviewed: 2026-05-11. Data sourced from public model cards and provider documentation.