LLM Reference

DeepSeek V3 Base vs Llama 3.1 405B Instruct

DeepSeek V3 Base (2024) and Llama 3.1 405B Instruct (2024) are compact production models from DeepSeek and AI at Meta. DeepSeek V3 Base ships a 128k-token context window, while Llama 3.1 405B Instruct ships a 128k-token context window. This comparison covers specs, pricing, API access, capabilities, benchmarks, input and output token costs, and production fit for coding and agent workloads.

DeepSeek V3 Base is safer overall; choose Llama 3.1 405B Instruct when provider fit matters.

Decision scorecard

Local evidence first
SignalDeepSeek V3 BaseLlama 3.1 405B Instruct
Best forgeneral production evaluationprovider-routed production
Decision fitLong contextRAG, Long context, and Classification
Context window128k128k
Cheapest output-$2.40/1M tokens
Provider routes0 tracked11 tracked
Shared benchmarks0 shared0 shared

Decision tradeoffs

Choose DeepSeek V3 Base when...
  • Local decision data tags DeepSeek V3 Base for Long context.
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.

Monthly cost at traffic

Estimate token spend from the cheapest tracked input and output route or tier on this page.

DeepSeek V3 Base

Unavailable

No complete token price in local provider data

Llama 3.1 405B Instruct

$2,520

Cheapest tracked route/tier: AWS Bedrock

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

Switch friction

DeepSeek V3 Base -> Llama 3.1 405B Instruct
  • No overlapping tracked provider route is sourced for DeepSeek V3 Base and Llama 3.1 405B Instruct; plan for SDK, billing, or endpoint changes.
  • Llama 3.1 405B Instruct adds Structured outputs in local capability data.
Llama 3.1 405B Instruct -> DeepSeek V3 Base
  • No overlapping tracked provider route is sourced for Llama 3.1 405B Instruct and DeepSeek V3 Base; plan for SDK, billing, or endpoint changes.
  • Check replacement coverage for Structured outputs before moving production traffic.

Specs

Specification
Released2024-12-262024-07-23
Context window128k128k
Parameters671B total, 37B active (MoE)405B
ArchitectureMixture of ExpertsDecoder Only
LicenseMITOSI-approvedLlama 3 Community
OpennessOpen sourceOpen weights
Commercial useCommercial use: permittedCommercial use: conditional
Knowledge cutoff2024-072023-12

Pricing and availability

Pricing attributeDeepSeek V3 BaseLlama 3.1 405B Instruct
Input price-$2.40/1M tokens
Output price-$2.40/1M tokens
Providers-

Capabilities

CapabilityDeepSeek V3 BaseLlama 3.1 405B Instruct
VisionNoNo
MultimodalNoNo
ReasoningNoNo
Function callingNoNo
Tool useNoNo
Structured outputsNoYes
Code executionNoNo
IDE integrationNoNo
Computer useNoNo
Parallel agentsNoNo

Benchmarks

No shared benchmark scores are currently available for this pair.

Deep dive

The capability footprint differs most on 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: DeepSeek V3 Base has no token price sourced yet and Llama 3.1 405B Instruct has $2.40/1M input tokens. Provider availability is 0 tracked routes versus 11. Treat unknown pricing as an integration gap, then verify the route you will actually call before estimating production spend.

Choose DeepSeek V3 Base when provider fit are central to the workload. Choose Llama 3.1 405B 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. 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, DeepSeek V3 Base or Llama 3.1 405B Instruct?

DeepSeek V3 Base supports 128k tokens, while Llama 3.1 405B 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 DeepSeek V3 Base or Llama 3.1 405B Instruct open source?

DeepSeek V3 Base is listed under MIT. Llama 3.1 405B Instruct is listed under Llama 3 Community. 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, DeepSeek V3 Base or Llama 3.1 405B Instruct?

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 DeepSeek V3 Base and Llama 3.1 405B Instruct?

DeepSeek V3 Base is available on the tracked providers still being sourced. Llama 3.1 405B Instruct is available on OctoAI API (Deprecated), Together AI, Fireworks AI, IBM watsonx, and Scale AI GenAI Platform. Provider coverage can affect latency, region availability, compliance posture, and fallback options.

When should I pick DeepSeek V3 Base over Llama 3.1 405B Instruct?

DeepSeek V3 Base is safer overall; choose Llama 3.1 405B Instruct when provider fit matters. If your workload also depends on provider fit, start with DeepSeek V3 Base; if it depends on provider fit, run the same evaluation with Llama 3.1 405B Instruct.

Continue comparing

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