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 | 7 tracked | 18 tracked |
| Shared benchmarks | MMLU PRO leader | 1 shared |
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 route 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 DeepInfra; 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 | MITOSI-approved | Llama 3 Community |
| Openness | Open source | Open weights |
| Weights | Unknown | Available |
| Code | Unknown | Unknown |
| Commercial use | Commercial use: permitted | Commercial use: conditional |
| 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 |
| JSON / 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 |
Continue comparing
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- DeepSeek V4 Flash vs Llama 3 70B Instruct
- Llama 3 70B Instruct vs Qwen3.6-35B-A3B
- DeepSeek R1 0528 vs Grok 4
- DeepSeek R1 0528 vs DeepSeek V4 Flash
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Last reviewed: 2026-07-11. Data sourced from public model cards and provider documentation.