Llama 3.3 70B vs Qwen2.5-72B
Llama 3.3 70B (2025) and Qwen2.5-72B (2025) are compact production models from AI at Meta and Alibaba. Llama 3.3 70B ships a 8K-token context window, while Qwen2.5-72B ships a 128k-token context window. On MMLU PRO, Qwen2.5-72B leads by a hair. This comparison covers specs, pricing, capabilities, benchmarks, provider availability, and production fit. It focuses on practical selection signals rather than broad model-family marketing.
Qwen2.5-72B fits 16x more tokens; pick it for long-context work and Llama 3.3 70B for tighter calls.
Specs
| Released | 2025-12-09 | 2025-10-10 |
| Context window | 8K | 128k |
| Parameters | 70B | 72B |
| Architecture | decoder only | - |
| License | True | Open Source |
| Knowledge cutoff | 2024-12 | 2024-09 |
Pricing and availability
| Llama 3.3 70B | Qwen2.5-72B | |
|---|---|---|
| Input price | $0.9/1M tokens | - |
| Output price | $0.9/1M tokens | - |
| Providers | - |
Capabilities
| Llama 3.3 70B | Qwen2.5-72B | |
|---|---|---|
| Vision | ||
| Multimodal | ||
| Reasoning | ||
| Function calling | ||
| Tool use | ||
| Structured outputs | ||
| Code execution |
Benchmarks
| Benchmark | Llama 3.3 70B | Qwen2.5-72B |
|---|---|---|
| MMLU PRO | 71.3 | 72.0 |
Deep dive
On shared benchmark coverage, MMLU PRO has Llama 3.3 70B at 71.3 and Qwen2.5-72B at 72, with Qwen2.5-72B ahead by 0.7 points. The largest visible gap is 0.7 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 vision: Llama 3.3 70B and multimodal input: Llama 3.3 70B. Both models share 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.
Pricing coverage is uneven: Llama 3.3 70B has $0.9/1M input tokens and Qwen2.5-72B has no token price sourced yet. Provider availability is 1 tracked routes versus 0. Treat unknown pricing as an integration gap, then verify the route you will actually call before estimating production spend.
Choose Llama 3.3 70B when vision-heavy evaluation and broader provider choice are central to the workload. Choose Qwen2.5-72B when long-context analysis and larger context windows 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, Llama 3.3 70B or Qwen2.5-72B?
Qwen2.5-72B supports 128k 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.
Is Llama 3.3 70B or Qwen2.5-72B open source?
Llama 3.3 70B is listed under True. Qwen2.5-72B 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, Llama 3.3 70B or Qwen2.5-72B?
Llama 3.3 70B 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, Llama 3.3 70B or Qwen2.5-72B?
Llama 3.3 70B 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.
Which is better for function calling, Llama 3.3 70B or Qwen2.5-72B?
Both Llama 3.3 70B and Qwen2.5-72B expose function calling. The better choice depends on benchmark fit, context budget, pricing, and whether your provider route exposes the same capability surface. Use this as a quick comparison signal, then confirm the provider-specific limits before committing to production.
Where can I run Llama 3.3 70B and Qwen2.5-72B?
Llama 3.3 70B is available on Fireworks AI. Qwen2.5-72B is available on the tracked providers still being sourced. Provider coverage can affect latency, region availability, compliance posture, and fallback options.
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Last reviewed: 2026-04-18. Data sourced from public model cards and provider documentation.