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Llama 3.1 405B Instruct vs Qwen3-105B

Llama 3.1 405B Instruct (2024) and Qwen3-105B (2025) are compact production models from AI at Meta and Alibaba. Llama 3.1 405B Instruct ships a 128K-token context window, while Qwen3-105B ships a 128k-token context window. This comparison covers specs, pricing, capabilities, benchmarks, provider availability, and production fit. It focuses on practical selection signals rather than broad model-family marketing. The goal is to make the tradeoff clear before deeper testing.

Qwen3-105B is safer overall; choose Llama 3.1 405B Instruct when provider fit matters.

Decision scorecard

Local evidence first
SignalLlama 3.1 405B InstructQwen3-105B
Decision fitRAG, Long context, and ClassificationRAG, Agents, and Long context
Context window128K128k
Cheapest output$2.4/1M tokens-
Provider routes11 tracked0 tracked
Shared benchmarks0 rows0 rows

Decision tradeoffs

Choose Llama 3.1 405B Instruct when...
  • Llama 3.1 405B Instruct has broader tracked provider coverage for fallback and procurement flexibility.
  • Llama 3.1 405B Instruct uniquely exposes Structured outputs in local model data.
  • Local decision data tags Llama 3.1 405B Instruct for RAG, Long context, and Classification.
Choose Qwen3-105B when...
  • Qwen3-105B uniquely exposes Function calling and Tool use in local model data.
  • Local decision data tags Qwen3-105B for RAG, Agents, and Long context.

Monthly cost at traffic

Estimate token spend from the cheapest tracked input and output prices on this page.

Llama 3.1 405B Instruct

$2,520

Cheapest tracked route: AWS Bedrock

Qwen3-105B

Unavailable

No complete token price in local provider data

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

Switch friction

Llama 3.1 405B Instruct -> Qwen3-105B
  • No overlapping tracked provider route is sourced for Llama 3.1 405B Instruct and Qwen3-105B; plan for SDK, billing, or endpoint changes.
  • Check replacement coverage for Structured outputs before moving production traffic.
  • Qwen3-105B adds Function calling and Tool use in local capability data.
Qwen3-105B -> Llama 3.1 405B Instruct
  • No overlapping tracked provider route is sourced for Qwen3-105B and Llama 3.1 405B Instruct; plan for SDK, billing, or endpoint changes.
  • Check replacement coverage for Function calling and Tool use before moving production traffic.
  • Llama 3.1 405B Instruct adds Structured outputs in local capability data.

Specs

Specification
Released2024-07-232025-12-15
Context window128K128k
Parameters405B105B
Architecturedecoder only-
LicenseOpen SourceOpen Source
Knowledge cutoff-2025-02

Pricing and availability

Pricing attributeLlama 3.1 405B InstructQwen3-105B
Input price$2.4/1M tokens-
Output price$2.4/1M tokens-
Providers-

Capabilities

CapabilityLlama 3.1 405B InstructQwen3-105B
VisionNoNo
MultimodalNoNo
ReasoningNoNo
Function callingNoYes
Tool useNoYes
Structured outputsYesNo
Code executionNoNo

Benchmarks

No shared benchmark rows are currently sourced for this pair.

Deep dive

The capability footprint differs most on function calling: Qwen3-105B, tool use: Qwen3-105B, and structured outputs: Llama 3.1 405B 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 Instruct has $2.4/1M input tokens and Qwen3-105B has no token price sourced yet. Provider availability is 11 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 3.1 405B Instruct when provider fit and broader provider choice are central to the workload. Choose Qwen3-105B when provider fit are more important. For production, rerun your own prompts through the exact provider, region, and tool stack you plan to ship. This keeps the decision grounded in measurable tradeoffs instead of brand-level assumptions. It also helps separate model capability from provider packaging, which can change cost and latency. For teams standardizing a stack, that distinction is often the difference between a benchmark win and a reliable deployment.

FAQ

Which has a larger context window, Llama 3.1 405B Instruct or Qwen3-105B?

Llama 3.1 405B Instruct supports 128K tokens, while Qwen3-105B 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 Instruct or Qwen3-105B open source?

Llama 3.1 405B Instruct is listed under Open Source. Qwen3-105B 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 function calling, Llama 3.1 405B Instruct or Qwen3-105B?

Qwen3-105B has the clearer documented function calling signal in this comparison. If function calling is mission-critical, validate it against the provider endpoint because model-level support and API-level exposure can differ.

Which is better for tool use, Llama 3.1 405B Instruct or Qwen3-105B?

Qwen3-105B has the clearer documented tool use signal in this comparison. If tool use is mission-critical, validate it against the provider endpoint because model-level support and API-level exposure can differ.

Which is better for structured outputs, Llama 3.1 405B Instruct or Qwen3-105B?

Llama 3.1 405B 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 Instruct and Qwen3-105B?

Llama 3.1 405B Instruct is available on OctoAI API (Deprecated), Together AI, Fireworks AI, IBM watsonx, and Scale AI GenAI Platform. Qwen3-105B is available on the tracked providers still being sourced. Provider coverage can affect latency, region availability, compliance posture, and fallback options.

Continue comparing

Last reviewed: 2026-05-16. Data sourced from public model cards and provider documentation.