DeepSeek V3 Base vs Llama 3 Taiwan 70B Instruct
DeepSeek V3 Base (2024) and Llama 3 Taiwan 70B Instruct (2024) are compact production models from DeepSeek and AI at Meta. DeepSeek V3 Base ships a 128K-token context window, while Llama 3 Taiwan 70B Instruct ships a 8K-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.
DeepSeek V3 Base fits 16x more tokens; pick it for long-context work and Llama 3 Taiwan 70B Instruct for tighter calls.
Specs
| Released | 2024-12-26 | 2024-07-01 |
| Context window | 128K | 8K |
| Parameters | — | 70B |
| Architecture | mixture of experts | decoder only |
| License | Open Source | 1 |
| Knowledge cutoff | - | - |
Pricing and availability
| DeepSeek V3 Base | Llama 3 Taiwan 70B Instruct | |
|---|---|---|
| Input price | - | - |
| Output price | - | - |
| Providers | - |
Pricing not yet sourced for either model.
Capabilities
| DeepSeek V3 Base | Llama 3 Taiwan 70B Instruct | |
|---|---|---|
| Vision | ||
| Multimodal | ||
| Reasoning | ||
| Function calling | ||
| Tool use | ||
| Structured outputs | ||
| Code execution |
Benchmarks
No shared benchmark rows are currently sourced for this pair.
Deep dive
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: DeepSeek V3 Base has no token price sourced yet and Llama 3 Taiwan 70B Instruct has no token price sourced yet. Provider availability is 0 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 Base when long-context analysis and larger context windows are central to the workload. Choose Llama 3 Taiwan 70B 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.
FAQ
Which has a larger context window, DeepSeek V3 Base or Llama 3 Taiwan 70B Instruct?
DeepSeek V3 Base supports 128K 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 Base or Llama 3 Taiwan 70B Instruct open source?
DeepSeek V3 Base is listed under Open Source. Llama 3 Taiwan 70B Instruct is listed under 1. 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 DeepSeek V3 Base and Llama 3 Taiwan 70B Instruct?
DeepSeek V3 Base is available on the tracked providers still being sourced. Llama 3 Taiwan 70B Instruct is available on NVIDIA NIM. Provider coverage can affect latency, region availability, compliance posture, and fallback options.
When should I pick DeepSeek V3 Base over Llama 3 Taiwan 70B Instruct?
DeepSeek V3 Base fits 16x more tokens; pick it for long-context work and Llama 3 Taiwan 70B Instruct for tighter calls. If your workload also depends on long-context analysis, start with DeepSeek V3 Base; if it depends on provider fit, run the same evaluation with Llama 3 Taiwan 70B Instruct.
Continue comparing
Last reviewed: 2026-04-15. Data sourced from public model cards and provider documentation.