LLM Reference

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
SignalLlama 3.1 405BQwen2.5-72B
Best forgeneral production evaluationprovider-routed production
Decision fitCoding, Long context, and ClassificationCoding, Long context, and Classification
Context window128k128k
Cheapest output-$0.60/1M tokens
Provider routes0 tracked2 tracked
Shared benchmarksGoogle-Proof Q&A leader4 shared

Decision tradeoffs

Choose Llama 3.1 405B when...
  • 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.
Choose Qwen2.5-72B when...
  • 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

Llama 3.1 405B -> Qwen2.5-72B
  • No overlapping tracked provider route is sourced for Llama 3.1 405B and Qwen2.5-72B; plan for SDK, billing, or endpoint changes.
Qwen2.5-72B -> Llama 3.1 405B
  • 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
Released2024-07-232024-06-07
Context window128k128k
Parameters405B72.7B
ArchitectureDecoder OnlyDecoder Only
LicenseLlama 3 CommunityApache 2.0OSI-approved
OpennessOpen weightsOpen source
WeightsAvailableAvailable
CodeUnknownUnknown
Commercial useCommercial use: conditionalCommercial use: permitted
Knowledge cutoff2023-12-

Pricing and availability

Pricing attributeLlama 3.1 405BQwen2.5-72B
Input price-$0.20/1M tokens
Output price-$0.60/1M tokens
Providers-

Capabilities

CapabilityLlama 3.1 405BQwen2.5-72B
VisionNoNo
MultimodalNoNo
ReasoningNoNo
Function callingNoNo
Tool useNoNo
Structured outputsNoNo
Code executionNoNo
IDE integrationNoNo
Computer useNoNo
Parallel agentsNoNo

Benchmarks

BenchmarkLlama 3.1 405BQwen2.5-72B
Google-Proof Q&A51.538.4
HumanEval89.059.1
HellaSwag95.887.6
Massive Multitask Language Understanding88.686.1

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.

Continue comparing

Last reviewed: 2026-07-09. Data sourced from public model cards and provider documentation.