Llama 3.1 405B vs Qwen2.5-72B
Llama 3.1 405B (2024) and Qwen2.5-72B (2024) are compact production models from AI at Meta and Alibaba. Llama 3.1 405B ships a 128k-token context window, while Qwen2.5-72B ships a 128k-token context window. On Google-Proof Q&A, Llama 3.1 405B leads by 13.1 pts. This comparison covers specs, pricing, API access, capabilities, benchmarks, input and output token costs, and production fit for coding and agent workloads.
Llama 3.1 405B is safer overall; choose Qwen2.5-72B when provider fit matters.
Decision scorecard
Local evidence first| Signal | Llama 3.1 405B | Qwen2.5-72B |
|---|---|---|
| Best for | general production evaluation | provider-routed production |
| Decision fit | Coding, Long context, and Classification | Coding, Long context, and Classification |
| Context window | 128k | 128k |
| Cheapest output | - | $0.60/1M tokens |
| Provider routes | 0 tracked | 2 tracked |
| Shared benchmarks | Google-Proof Q&A leader | 4 shared |
Decision tradeoffs
- Llama 3.1 405B holds a shared-benchmark lead on Google-Proof Q&A, ahead by 13.1 points.
- Local decision data tags Llama 3.1 405B for Coding, Long context, and Classification.
- Qwen2.5-72B has broader tracked provider coverage for fallback and procurement flexibility.
- Local decision data tags Qwen2.5-72B for Coding, Long context, and Classification.
Monthly cost at traffic
Estimate token spend from the cheapest tracked input and output route or tier on this page.
Llama 3.1 405B
Unavailable
No complete token price in local provider data
Qwen2.5-72B
$310
Cheapest tracked route/tier: Bitdeer AI
Cost delta unavailable until both models have sourced input and output token prices.
Switch friction
- No overlapping tracked provider route is sourced for Llama 3.1 405B and Qwen2.5-72B; plan for SDK, billing, or endpoint changes.
- No overlapping tracked provider route is sourced for Qwen2.5-72B and Llama 3.1 405B; plan for SDK, billing, or endpoint changes.
Specs
| Specification | ||
|---|---|---|
| Released | 2024-07-23 | 2024-06-07 |
| Context window | 128k | 128k |
| Parameters | 405B | 72.7B |
| Architecture | Decoder Only | Decoder Only |
| License | Llama 3 Community | Apache 2.0OSI-approved |
| Openness | Open weights | Open source |
| Weights | Available | Available |
| Code | Unknown | Unknown |
| Commercial use | Commercial use: conditional | Commercial use: permitted |
| Knowledge cutoff | 2023-12 | - |
Pricing and availability
| Pricing attribute | Llama 3.1 405B | Qwen2.5-72B |
|---|---|---|
| Input price | - | $0.20/1M tokens |
| Output price | - | $0.60/1M tokens |
| Providers | - |
Capabilities
| Capability | Llama 3.1 405B | Qwen2.5-72B |
|---|---|---|
| Vision | No | No |
| Multimodal | No | No |
| Reasoning | No | No |
| Function calling | No | No |
| Tool use | No | No |
| Structured outputs | No | No |
| Code execution | No | No |
| IDE integration | No | No |
| Computer use | No | No |
| Parallel agents | No | No |
Benchmarks
| Benchmark | Llama 3.1 405B | Qwen2.5-72B |
|---|---|---|
| Google-Proof Q&A | 51.5 | 38.4 |
| HumanEval | 89.0 | 59.1 |
| HellaSwag | 95.8 | 87.6 |
| Massive Multitask Language Understanding | 88.6 | 86.1 |
Deep dive
On shared benchmark coverage, Google-Proof Q&A has Llama 3.1 405B at 51.5 and Qwen2.5-72B at 38.4, with Llama 3.1 405B ahead by 13.1 points; HumanEval has Llama 3.1 405B at 89 and Qwen2.5-72B at 59.1, with Llama 3.1 405B ahead by 29.9 points; HellaSwag has Llama 3.1 405B at 95.8 and Qwen2.5-72B at 87.6, with Llama 3.1 405B ahead by 8.2 points. The largest visible gap is 29.9 points on HumanEval, 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 is close: both models cover the core production surface. That makes context budget, benchmark fit, and provider maturity more important than a simple checklist. If your application depends on one integration detail, verify it against the provider route you plan to use, not just the base model listing.
Pricing coverage is uneven: Llama 3.1 405B has no token price sourced yet and Qwen2.5-72B has $0.20/1M input tokens. Provider availability is 0 tracked routes versus 2. Treat unknown pricing as an integration gap, then verify the route you will actually call before estimating production spend.
Choose Llama 3.1 405B when provider fit are central to the workload. Choose Qwen2.5-72B when provider fit 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, Llama 3.1 405B or Qwen2.5-72B?
Llama 3.1 405B supports 128k tokens, while Qwen2.5-72B supports 128k tokens. That gap matters most for long documents, large codebases, retrieval-heavy agents, and conversations where earlier context must remain visible.
Is Llama 3.1 405B or Qwen2.5-72B open source?
Llama 3.1 405B is listed under Llama 3 Community. Qwen2.5-72B is listed under Apache 2.0. License labels affect whether you can self-host, redistribute weights, or rely only on hosted APIs, so confirm the upstream license before deployment.
Where can I run Llama 3.1 405B and Qwen2.5-72B?
Llama 3.1 405B is available on the tracked providers still being sourced. Qwen2.5-72B is available on Fireworks AI and Bitdeer AI. Provider coverage can affect latency, region availability, compliance posture, and fallback options.
When should I pick Llama 3.1 405B over Qwen2.5-72B?
Llama 3.1 405B is safer overall; choose Qwen2.5-72B when provider fit matters. If your workload also depends on provider fit, start with Llama 3.1 405B; if it depends on provider fit, run the same evaluation with Qwen2.5-72B.
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Last reviewed: 2026-07-09. Data sourced from public model cards and provider documentation.