LLM Reference

DeepSeek V3 vs Llama 3 Taiwan 70B Instruct

DeepSeek V3 (2024) and Llama 3 Taiwan 70B Instruct (2024) are compact production models from DeepSeek and AI at Meta. DeepSeek V3 ships a 64k-token context window, while Llama 3 Taiwan 70B Instruct ships a 8k-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 fits 8x more tokens; pick it for long-context work and Llama 3 Taiwan 70B Instruct for tighter calls.

Decision scorecard

Local evidence first
SignalDeepSeek V3Llama 3 Taiwan 70B Instruct
Best fortool-calling agents and provider-routed productiongeneral production evaluation
Decision fitCoding, Agents, and ClassificationGeneral
Context window64k8k
Cheapest output$0.30/1M tokens-
Provider routes13 tracked1 tracked
Shared benchmarks0 rows0 rows

Decision tradeoffs

Choose DeepSeek V3 when...
  • DeepSeek V3 has the larger context window for long prompts, retrieval packs, or transcript analysis.
  • DeepSeek V3 has broader tracked provider coverage for fallback and procurement flexibility.
  • DeepSeek V3 uniquely exposes Function calling, Tool use, and Structured outputs in local model data.
  • Local decision data tags DeepSeek V3 for Coding, Agents, and Classification.
Choose Llama 3 Taiwan 70B Instruct when...
  • Use Llama 3 Taiwan 70B Instruct when your own prompt tests beat the comparison signals; the local data does not show a decisive standalone advantage yet.

Monthly cost at traffic

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

DeepSeek V3

$155

Cheapest tracked route/tier: Bitdeer AI

Llama 3 Taiwan 70B Instruct

Unavailable

No complete token price in local provider data

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

Switch friction

DeepSeek V3 -> Llama 3 Taiwan 70B Instruct
  • Provider overlap exists on NVIDIA NIM; start route-level A/B tests there.
  • Check replacement coverage for Function calling, Tool use, and Structured outputs before moving production traffic.
Llama 3 Taiwan 70B Instruct -> DeepSeek V3
  • Provider overlap exists on NVIDIA NIM; start route-level A/B tests there.
  • DeepSeek V3 adds Function calling, Tool use, and Structured outputs in local capability data.

Specs

Specification
Released2024-12-262024-07-01
Context window64k8k
Parameters671B70B
Architecturemixture of expertsdecoder only
LicenseMIT(OSI)Llama 3 Community
OpennessOpen sourceOpen weights
Commercial useCommercial use allowedCommercial use with conditions
Knowledge cutoff2024-042023-12

Pricing and availability

Pricing attributeDeepSeek V3Llama 3 Taiwan 70B Instruct
Input price$0.10/1M tokens-
Output price$0.30/1M tokens-
Providers

Capabilities

CapabilityDeepSeek V3Llama 3 Taiwan 70B Instruct
VisionNoNo
MultimodalNoNo
ReasoningNoNo
Function callingYesNo
Tool useYesNo
Structured outputsYesNo
Code executionNoNo
IDE integrationNoNo
Computer useNoNo
Parallel agentsNoNo

Benchmarks

No shared benchmark rows are currently sourced for this pair.

Deep dive

The capability footprint differs most on function calling: DeepSeek V3, tool use: DeepSeek V3, and structured outputs: DeepSeek V3. 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 has $0.10/1M input tokens and Llama 3 Taiwan 70B Instruct has no token price sourced yet. Provider availability is 13 tracked routes versus 1. Treat unknown pricing as an integration gap, then verify the route you will actually call before estimating production spend.

Choose DeepSeek V3 when long-context analysis, larger context windows, and broader provider choice are central to the workload. Choose Llama 3 Taiwan 70B Instruct 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.

FAQ

Which has a larger context window, DeepSeek V3 or Llama 3 Taiwan 70B Instruct?

DeepSeek V3 supports 64k tokens, while Llama 3 Taiwan 70B Instruct supports 8k tokens. That gap matters most for long documents, large codebases, retrieval-heavy agents, and conversations where earlier context must remain visible.

Is DeepSeek V3 or Llama 3 Taiwan 70B Instruct open source?

DeepSeek V3 is listed under MIT. Llama 3 Taiwan 70B 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 function calling, DeepSeek V3 or Llama 3 Taiwan 70B Instruct?

DeepSeek V3 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, DeepSeek V3 or Llama 3 Taiwan 70B Instruct?

DeepSeek V3 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, DeepSeek V3 or Llama 3 Taiwan 70B Instruct?

DeepSeek V3 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 and Llama 3 Taiwan 70B Instruct?

DeepSeek V3 is available on DeepInfra, Fireworks AI, DeepSeek Platform, Microsoft Foundry, and OpenRouter. Llama 3 Taiwan 70B Instruct is available on NVIDIA NIM. Provider coverage can affect latency, region availability, compliance posture, and fallback options.

Continue comparing

Last reviewed: 2026-05-22. Data sourced from public model cards and provider documentation.