DeepSeek V3.1 vs Llama 3 Taiwan 70B Instruct
DeepSeek V3.1 (2025) and Llama 3 Taiwan 70B Instruct (2024) are compact production models from DeepSeek and AI at Meta. DeepSeek V3.1 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 V3.1 fits 8x more tokens; pick it for long-context work and Llama 3 Taiwan 70B Instruct for tighter calls.
Decision scorecard
Local evidence first| Signal | DeepSeek V3.1 | Llama 3 Taiwan 70B Instruct |
|---|---|---|
| Best for | multimodal apps and provider-routed production | general production evaluation |
| Decision fit | Coding, Agents, and Vision | General |
| Context window | 64k | 8k |
| Cheapest output | $1/1M tokens | - |
| Provider routes | 8 tracked | 1 tracked |
| Shared benchmarks | 0 rows | 0 rows |
Decision tradeoffs
- DeepSeek V3.1 has the larger context window for long prompts, retrieval packs, or transcript analysis.
- DeepSeek V3.1 has broader tracked provider coverage for fallback and procurement flexibility.
- DeepSeek V3.1 uniquely exposes Vision, Multimodal, and Structured outputs in local model data.
- Local decision data tags DeepSeek V3.1 for Coding, Agents, and Vision.
- 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 V3.1
$466
Cheapest tracked route/tier: Novita 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
- Provider overlap exists on NVIDIA NIM; start route-level A/B tests there.
- Check replacement coverage for Vision, Multimodal, and Structured outputs before moving production traffic.
- Provider overlap exists on NVIDIA NIM; start route-level A/B tests there.
- DeepSeek V3.1 adds Vision, Multimodal, and Structured outputs in local capability data.
Specs
| Specification | ||
|---|---|---|
| Released | 2025-08-21 | 2024-07-01 |
| Context window | 64k | 8k |
| Parameters | 671B total, 37B active (MoE) | 70B |
| Architecture | mixture of experts | decoder only |
| License | MIT(OSI) | Llama 3 Community |
| Openness | Open source | Open weights |
| Commercial use | Commercial use allowed | Commercial use with conditions |
| Knowledge cutoff | - | 2023-12 |
Pricing and availability
| Pricing attribute | DeepSeek V3.1 | Llama 3 Taiwan 70B Instruct |
|---|---|---|
| Input price | $0.27/1M tokens | - |
| Output price | $1/1M tokens | - |
| Providers |
Capabilities
| Capability | DeepSeek V3.1 | Llama 3 Taiwan 70B Instruct |
|---|---|---|
| Vision | Yes | No |
| Multimodal | Yes | No |
| Reasoning | No | No |
| Function calling | No | No |
| Tool use | No | No |
| Structured outputs | Yes | No |
| Code execution | Yes | No |
| IDE integration | No | No |
| Computer use | No | No |
| Parallel agents | No | No |
Benchmarks
No shared benchmark rows are currently sourced for this pair.
Deep dive
The capability footprint differs most on vision: DeepSeek V3.1, multimodal input: DeepSeek V3.1, structured outputs: DeepSeek V3.1, and code execution: DeepSeek V3.1. 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 V3.1 has $0.27/1M input tokens and Llama 3 Taiwan 70B Instruct has no token price sourced yet. Provider availability is 8 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 V3.1 when coding workflow support, 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 V3.1 or Llama 3 Taiwan 70B Instruct?
DeepSeek V3.1 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 V3.1 or Llama 3 Taiwan 70B Instruct open source?
DeepSeek V3.1 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 vision, DeepSeek V3.1 or Llama 3 Taiwan 70B Instruct?
DeepSeek V3.1 has the clearer documented vision signal in this comparison. If vision is mission-critical, validate it against the provider endpoint because model-level support and API-level exposure can differ. Use this as a quick comparison signal, then confirm the provider-specific limits before committing to production.
Which is better for multimodal input, DeepSeek V3.1 or Llama 3 Taiwan 70B Instruct?
DeepSeek V3.1 has the clearer documented multimodal input signal in this comparison. If multimodal input 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 V3.1 or Llama 3 Taiwan 70B Instruct?
DeepSeek V3.1 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 V3.1 and Llama 3 Taiwan 70B Instruct?
DeepSeek V3.1 is available on Microsoft Foundry, Fireworks AI, NVIDIA NIM, Together AI, and AWS Bedrock. 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.