DeepSeek R1 0528 vs Llama 3 70B Instruct
DeepSeek R1 0528 (2025) and Llama 3 70B Instruct (2024) are frontier reasoning models from DeepSeek and AI at Meta. DeepSeek R1 0528 ships a 130k-token context window, while Llama 3 70B Instruct ships a 8k-token context window. On MMLU PRO, DeepSeek R1 0528 leads by 27.6 pts. This comparison covers specs, pricing, API access, capabilities, benchmarks, input and output token costs, and production fit for coding and agent workloads.
DeepSeek R1 0528 fits 16x more tokens; pick it for long-context work and Llama 3 70B Instruct for tighter calls.
Decision scorecard
Local evidence first| Signal | DeepSeek R1 0528 | Llama 3 70B Instruct |
|---|---|---|
| Best for | reasoning-heavy apps and provider-routed production | provider-routed production |
| Decision fit | Coding, RAG, and Agents | Coding, Classification, and JSON / Tool use |
| Context window | 130k | 8k |
| Cheapest output | $2.15/1M tokens | $0.40/1M tokens |
| Provider routes | 6 tracked | 18 tracked |
| Shared benchmarks | MMLU PRO leader | 1 rows |
Decision tradeoffs
- DeepSeek R1 0528 holds a shared-benchmark lead on MMLU PRO, ahead by 27.6 points.
- DeepSeek R1 0528 has the larger context window for long prompts, retrieval packs, or transcript analysis.
- DeepSeek R1 0528 uniquely exposes Reasoning and Code execution in local model data.
- Local decision data tags DeepSeek R1 0528 for Coding, RAG, and Agents.
- Llama 3 70B Instruct has the lower cheapest tracked output price at $0.40/1M tokens.
- Llama 3 70B Instruct has broader tracked provider coverage for fallback and procurement flexibility.
- Local decision data tags Llama 3 70B Instruct for Coding, Classification, and JSON / Tool use.
Monthly cost at traffic
Estimate token spend from the cheapest tracked input and output route or tier on this page.
DeepSeek R1 0528
$938
Cheapest tracked route/tier: OpenRouter
Llama 3 70B Instruct
$420
Cheapest tracked route/tier: Hyperbolic AI Inference
Estimated monthly gap: $518. Batch, cache, alternate speed tiers, and negotiated pricing are excluded from this local estimate.
Switch friction
- Provider overlap exists on GCP Vertex AI, Microsoft Foundry, and Fireworks AI; start route-level A/B tests there.
- Llama 3 70B Instruct is $1.75/1M tokens lower on cheapest tracked output pricing before cache, batch, or negotiated discounts.
- Check replacement coverage for Reasoning and Code execution before moving production traffic.
- Provider overlap exists on Together AI, Fireworks AI, and GCP Vertex AI; start route-level A/B tests there.
- DeepSeek R1 0528 is $1.75/1M tokens higher on cheapest tracked output pricing, so quality gains need to justify the spend.
- DeepSeek R1 0528 adds Reasoning and Code execution in local capability data.
Specs
| Specification | ||
|---|---|---|
| Released | 2025-05-28 | 2024-04-18 |
| Context window | 130k | 8k |
| Parameters | 685B total, 37B active (MoE) | 70B |
| Architecture | decoder only | 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 R1 0528 | Llama 3 70B Instruct |
|---|---|---|
| Input price | $0.50/1M tokens | $0.40/1M tokens |
| Output price | $2.15/1M tokens | $0.40/1M tokens |
| Providers |
Capabilities
| Capability | DeepSeek R1 0528 | Llama 3 70B Instruct |
|---|---|---|
| Vision | No | No |
| Multimodal | No | No |
| Reasoning | Yes | No |
| Function calling | No | No |
| Tool use | No | No |
| Structured outputs | Yes | Yes |
| Code execution | Yes | No |
| IDE integration | No | No |
| Computer use | No | No |
| Parallel agents | No | No |
Benchmarks
| Benchmark | DeepSeek R1 0528 | Llama 3 70B Instruct |
|---|---|---|
| MMLU PRO | 85.0 | 57.4 |
Deep dive
On shared benchmark coverage, MMLU PRO has DeepSeek R1 0528 at 85 and Llama 3 70B Instruct at 57.4, with DeepSeek R1 0528 ahead by 27.6 points. The largest visible gap is 27.6 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 R1 0528 and code execution: DeepSeek R1 0528. 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 R1 0528 lists $0.50/1M input and $2.15/1M output tokens on the cheapest tracked provider, while Llama 3 70B Instruct lists $0.40/1M input and $0.40/1M output tokens on the cheapest tracked provider. A 70/30 input-output blend puts Llama 3 70B Instruct lower by about $0.59 per million blended tokens. Availability is 6 providers versus 18, so concentration risk also matters.
Choose DeepSeek R1 0528 when coding workflow support and larger context windows are central to the workload. Choose Llama 3 70B Instruct when provider fit, lower input-token cost, 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 R1 0528 or Llama 3 70B Instruct?
DeepSeek R1 0528 supports 130k tokens, while Llama 3 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.
Which is cheaper, DeepSeek R1 0528 or Llama 3 70B Instruct?
Llama 3 70B Instruct is cheaper on tracked token pricing. DeepSeek R1 0528 costs $0.50/1M input and $2.15/1M output tokens. Llama 3 70B Instruct costs $0.40/1M input and $0.40/1M output tokens. Provider discounts or batch pricing can still change the final bill.
Is DeepSeek R1 0528 or Llama 3 70B Instruct open source?
DeepSeek R1 0528 is listed under MIT. Llama 3 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 reasoning mode, DeepSeek R1 0528 or Llama 3 70B Instruct?
DeepSeek R1 0528 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 structured outputs, DeepSeek R1 0528 or Llama 3 70B Instruct?
Both DeepSeek R1 0528 and Llama 3 70B Instruct expose structured outputs. The better choice depends on benchmark fit, context budget, pricing, and whether your provider route exposes the same capability surface.
Where can I run DeepSeek R1 0528 and Llama 3 70B Instruct?
DeepSeek R1 0528 is available on Together AI, Fireworks AI, GCP Vertex AI, Novita AI, and OpenRouter. Llama 3 70B Instruct is available on GCP Vertex AI, AWS Bedrock, Microsoft Foundry, NVIDIA NIM, and DeepInfra. 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.