DeepSeek V4 Pro vs Llama 3.1 405B Instruct
DeepSeek V4 Pro (2026) and Llama 3.1 405B Instruct (2024) are frontier reasoning models from DeepSeek and AI at Meta. DeepSeek V4 Pro ships a 1m-token context window, while Llama 3.1 405B Instruct ships a 128k-token context window. On Massive Multitask Language Understanding, DeepSeek V4 Pro leads by 1.5 pts. This comparison covers specs, pricing, API access, capabilities, benchmarks, input and output token costs, and production fit for coding and agent workloads.
DeepSeek V4 Pro is ~452% cheaper at $0.43/1M; pay for Llama 3.1 405B Instruct only for provider fit.
Decision scorecard
Local evidence first| Signal | DeepSeek V4 Pro | Llama 3.1 405B Instruct |
|---|---|---|
| Best for | reasoning-heavy apps, tool-calling agents, and long-context analysis | provider-routed production |
| Decision fit | Coding, RAG, and Agents | RAG, Long context, and Classification |
| Context window | 1m | 128k |
| Cheapest output | $0.87/1M tokens | $2.40/1M tokens |
| Provider routes | 5 tracked | 11 tracked |
| Shared benchmarks | Massive Multitask Language Understanding leader | 1 rows |
Decision tradeoffs
- DeepSeek V4 Pro holds a shared-benchmark lead on Massive Multitask Language Understanding, ahead by 1.5 points.
- DeepSeek V4 Pro has the larger context window for long prompts, retrieval packs, or transcript analysis.
- DeepSeek V4 Pro has the lower cheapest tracked output price at $0.87/1M tokens.
- DeepSeek V4 Pro uniquely exposes Reasoning, Function calling, and Tool use in local model data.
- Local decision data tags DeepSeek V4 Pro for Coding, RAG, and Agents.
- Llama 3.1 405B Instruct has broader tracked provider coverage for fallback and procurement flexibility.
- 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 V4 Pro
$566
Cheapest tracked route/tier: DeepSeek Platform
Llama 3.1 405B Instruct
$2,520
Cheapest tracked route/tier: AWS Bedrock
Estimated monthly gap: $1,955. Batch, cache, alternate speed tiers, and negotiated pricing are excluded from this local estimate.
Switch friction
- Provider overlap exists on Fireworks AI; start route-level A/B tests there.
- Llama 3.1 405B Instruct is $1.53/1M tokens higher on cheapest tracked output pricing, so quality gains need to justify the spend.
- Check replacement coverage for Reasoning, Function calling, and Tool use before moving production traffic.
- Provider overlap exists on Fireworks AI; start route-level A/B tests there.
- DeepSeek V4 Pro is $1.53/1M tokens lower on cheapest tracked output pricing before cache, batch, or negotiated discounts.
- DeepSeek V4 Pro adds Reasoning, Function calling, and Tool use in local capability data.
Specs
| Specification | ||
|---|---|---|
| Released | 2026-04-24 | 2024-07-23 |
| Context window | 1m | 128k |
| Parameters | 1.6T | 405B |
| Architecture | Mixture of Experts (MoE) with CSA+HCA hybrid attention | 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 V4 Pro | Llama 3.1 405B Instruct |
|---|---|---|
| Input price | $0.43/1M tokens | $2.40/1M tokens |
| Output price | $0.87/1M tokens | $2.40/1M tokens |
| Providers |
Capabilities
| Capability | DeepSeek V4 Pro | Llama 3.1 405B Instruct |
|---|---|---|
| Vision | No | No |
| Multimodal | No | No |
| Reasoning | Yes | No |
| Function calling | Yes | No |
| Tool use | Yes | No |
| Structured outputs | Yes | Yes |
| Code execution | No | No |
| IDE integration | No | No |
| Computer use | No | No |
| Parallel agents | No | No |
Benchmarks
| Benchmark | DeepSeek V4 Pro | Llama 3.1 405B Instruct |
|---|---|---|
| Massive Multitask Language Understanding | 90.1 | 88.6 |
Deep dive
On shared benchmark coverage, Massive Multitask Language Understanding has DeepSeek V4 Pro at 90.1 and Llama 3.1 405B Instruct at 88.6, with DeepSeek V4 Pro ahead by 1.5 points. The largest visible gap is 1.5 points on Massive Multitask Language Understanding, which matters most when that benchmark mirrors your workload. Treat isolated benchmark wins as directional, because provider routing, prompt style, and tool access can move real application results.
The capability footprint differs most on reasoning mode: DeepSeek V4 Pro, function calling: DeepSeek V4 Pro, and tool use: DeepSeek V4 Pro. Both models share structured outputs, 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.
For cost, DeepSeek V4 Pro lists $0.43/1M input and $0.87/1M output tokens on the cheapest tracked provider, while Llama 3.1 405B Instruct lists $2.40/1M input and $2.40/1M output tokens on the cheapest tracked provider. A 70/30 input-output blend puts DeepSeek V4 Pro lower by about $1.83 per million blended tokens. Availability is 5 providers versus 11, so concentration risk also matters.
Choose DeepSeek V4 Pro when reasoning depth, larger context windows, and lower input-token cost 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.
FAQ
Which has a larger context window, DeepSeek V4 Pro or Llama 3.1 405B Instruct?
DeepSeek V4 Pro supports 1m 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.
Which is cheaper, DeepSeek V4 Pro or Llama 3.1 405B Instruct?
DeepSeek V4 Pro is cheaper on tracked token pricing. DeepSeek V4 Pro costs $0.43/1M input and $0.87/1M output tokens. Llama 3.1 405B Instruct costs $2.40/1M input and $2.40/1M output tokens. Provider discounts or batch pricing can still change the final bill.
Is DeepSeek V4 Pro or Llama 3.1 405B Instruct open source?
DeepSeek V4 Pro 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 reasoning mode, DeepSeek V4 Pro or Llama 3.1 405B Instruct?
DeepSeek V4 Pro has the clearer documented reasoning mode signal in this comparison. If reasoning mode is mission-critical, validate it against the provider endpoint because model-level support and API-level exposure can differ.
Which is better for function calling, DeepSeek V4 Pro or Llama 3.1 405B Instruct?
DeepSeek V4 Pro 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.
Where can I run DeepSeek V4 Pro and Llama 3.1 405B Instruct?
DeepSeek V4 Pro is available on DeepSeek Platform, Fireworks AI, OpenRouter, Vercel AI Gateway, and Novita AI. 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.
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Last reviewed: 2026-05-31. Data sourced from public model cards and provider documentation.