LLM Reference

Llama 3.1 405B vs Qwen2.5-72B-Instruct

Llama 3.1 405B (2024) and Qwen2.5-72B-Instruct (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-Instruct 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-Instruct when provider fit matters.

Decision scorecard

Local evidence first
SignalLlama 3.1 405BQwen2.5-72B-Instruct
Best forgeneral production evaluationprovider-routed production
Decision fitCoding, Long context, and ClassificationCoding, RAG, and Long context
Context window128k128k
Cheapest output-$0.54/1M tokens
Provider routes0 tracked7 tracked
Shared benchmarksGoogle-Proof Q&A leader5 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-Instruct when...
  • Qwen2.5-72B-Instruct holds a shared-benchmark lead on Chatbot Arena, ahead by 42 points.
  • Qwen2.5-72B-Instruct has broader tracked provider coverage for fallback and procurement flexibility.
  • Qwen2.5-72B-Instruct uniquely exposes Structured outputs in local model data.
  • Local decision data tags Qwen2.5-72B-Instruct for Coding, RAG, and Long context.

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-Instruct

$279

Cheapest tracked route/tier: Chutes AI

Cost delta unavailable until both models have sourced input and output token prices.

Switch friction

Llama 3.1 405B -> Qwen2.5-72B-Instruct
  • No overlapping tracked provider route is sourced for Llama 3.1 405B and Qwen2.5-72B-Instruct; plan for SDK, billing, or endpoint changes.
  • Qwen2.5-72B-Instruct adds Structured outputs in local capability data.
Qwen2.5-72B-Instruct -> Llama 3.1 405B
  • No overlapping tracked provider route is sourced for Qwen2.5-72B-Instruct and Llama 3.1 405B; plan for SDK, billing, or endpoint changes.
  • Check replacement coverage for Structured outputs before moving production traffic.

Specs

Specification
Released2024-07-232024-06-07
Context window128k128k
Parameters405B72.7B
ArchitectureDecoder OnlyDecoder Only
LicenseLlama 3 CommunityApache 2.0OSI-approved
OpennessOpen weightsOpen source
Commercial useCommercial use: conditionalCommercial use: permitted
Knowledge cutoff2023-12-

Pricing and availability

Pricing attributeLlama 3.1 405BQwen2.5-72B-Instruct
Input price-$0.18/1M tokens
Output price-$0.54/1M tokens
Providers-

Capabilities

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

Benchmarks

BenchmarkLlama 3.1 405BQwen2.5-72B-Instruct
Google-Proof Q&A51.538.4
HumanEval89.086.6
Chatbot Arena1228.01270.0
Massive Multitask Language Understanding88.688.2
HellaSwag95.895.6

Deep dive

On shared benchmark coverage, Google-Proof Q&A has Llama 3.1 405B at 51.5 and Qwen2.5-72B-Instruct 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-Instruct at 86.6, with Llama 3.1 405B ahead by 2.4 points; Chatbot Arena has Llama 3.1 405B at 1228 and Qwen2.5-72B-Instruct at 1270, with Qwen2.5-72B-Instruct ahead by 42 points. The largest visible gap is 42 points on Chatbot Arena, 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: Qwen2.5-72B-Instruct. Both models share the core language-model surface, 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 3.1 405B has no token price sourced yet and Qwen2.5-72B-Instruct has $0.18/1M input tokens. Provider availability is 0 tracked routes versus 7. 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-Instruct 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-Instruct?

Llama 3.1 405B supports 128k tokens, while Qwen2.5-72B-Instruct 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-Instruct open source?

Llama 3.1 405B is listed under Llama 3 Community. Qwen2.5-72B-Instruct 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.

Which is better for structured outputs, Llama 3.1 405B or Qwen2.5-72B-Instruct?

Qwen2.5-72B-Instruct has the clearer documented structured outputs signal in this comparison. If structured outputs is mission-critical, validate it against the provider endpoint because model-level support and API-level exposure can differ.

Where can I run Llama 3.1 405B and Qwen2.5-72B-Instruct?

Llama 3.1 405B is available on the tracked providers still being sourced. Qwen2.5-72B-Instruct is available on DeepInfra, OpenRouter, Fireworks AI, Novita AI, and Chutes 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-Instruct?

Llama 3.1 405B is safer overall; choose Qwen2.5-72B-Instruct 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-Instruct.

Continue comparing

Last reviewed: 2026-06-15. Data sourced from public model cards and provider documentation.