DeepSeek V4 Pro vs Llama 3 8B Instruct
DeepSeek V4 Pro (2026) and Llama 3 8B Instruct (2024) are frontier reasoning models from DeepSeek and AI at Meta. DeepSeek V4 Pro ships a 1M-token context window, while Llama 3 8B Instruct ships a 8K-token context window. On MMLU PRO, DeepSeek V4 Pro leads by 47 pts. This comparison covers specs, pricing, capabilities, benchmarks, provider availability, and production fit.
DeepSeek V4 Pro fits 125x more tokens; pick it for long-context work and Llama 3 8B Instruct for tighter calls.
Specs
| Released | 2026-04-24 | 2024-04-18 |
| Context window | 1M | 8K |
| Parameters | 1.6T | 8B |
| Architecture | mixture of experts | decoder only |
| License | MIT | Open Source |
| Knowledge cutoff | - | - |
Pricing and availability
| DeepSeek V4 Pro | Llama 3 8B Instruct | |
|---|---|---|
| Input price | - | $0.03/1M tokens |
| Output price | - | $0.04/1M tokens |
| Providers | - |
Capabilities
| DeepSeek V4 Pro | Llama 3 8B Instruct | |
|---|---|---|
| Vision | ||
| Multimodal | ||
| Reasoning | ||
| Function calling | ||
| Tool use | ||
| Structured outputs | ||
| Code execution |
Benchmarks
| Benchmark | DeepSeek V4 Pro | Llama 3 8B Instruct |
|---|---|---|
| MMLU PRO | 87.5 | 40.5 |
| Google-Proof Q&A | 90.1 | 44.8 |
| Massive Multitask Language Understanding | 90.1 | 76.9 |
Deep dive
On shared benchmark coverage, MMLU PRO has DeepSeek V4 Pro at 87.5 and Llama 3 8B Instruct at 40.5, with DeepSeek V4 Pro ahead by 47 points; Google-Proof Q&A has DeepSeek V4 Pro at 90.1 and Llama 3 8B Instruct at 44.8, with DeepSeek V4 Pro ahead by 45.3 points; Massive Multitask Language Understanding has DeepSeek V4 Pro at 90.1 and Llama 3 8B Instruct at 76.9, with DeepSeek V4 Pro ahead by 13.2 points. The largest visible gap is 47 points on MMLU PRO, 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.
Pricing coverage is uneven: DeepSeek V4 Pro has no token price sourced yet and Llama 3 8B Instruct has $0.03/1M input tokens. Provider availability is 0 tracked routes versus 17. Treat unknown pricing as an integration gap, then verify the route you will actually call before estimating production spend.
Choose DeepSeek V4 Pro when reasoning depth and larger context windows are central to the workload. Choose Llama 3 8B 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 8B Instruct?
DeepSeek V4 Pro supports 1M tokens, while Llama 3 8B 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 V4 Pro or Llama 3 8B Instruct open source?
DeepSeek V4 Pro is listed under MIT. Llama 3 8B Instruct is listed under Open Source. 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 8B 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 8B 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.
Which is better for tool use, DeepSeek V4 Pro or Llama 3 8B Instruct?
DeepSeek V4 Pro 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.
Where can I run DeepSeek V4 Pro and Llama 3 8B Instruct?
DeepSeek V4 Pro is available on the tracked providers still being sourced. Llama 3 8B Instruct is available on AWS Bedrock, DeepInfra, OctoAI API, Fireworks AI, and Alibaba Cloud PAI-EAS. Provider coverage can affect latency, region availability, compliance posture, and fallback options.
Continue comparing
Last reviewed: 2026-04-24. Data sourced from public model cards and provider documentation.