DeepSeek R1 0528 vs Llama 3.3 70B
DeepSeek R1 0528 (2025) and Llama 3.3 70B (2025) are frontier reasoning models from DeepSeek and AI at Meta. DeepSeek R1 0528 ships a 130k-token context window, while Llama 3.3 70B ships a 8k-token context window. On MMLU PRO, DeepSeek R1 0528 leads by 13.7 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 is ~80% cheaper at $0.50/1M; pay for Llama 3.3 70B only for vision-heavy evaluation.
Decision scorecard
Local evidence first| Signal | DeepSeek R1 0528 | Llama 3.3 70B |
|---|---|---|
| Best for | reasoning-heavy apps and provider-routed production | multimodal apps and tool-calling agents |
| Decision fit | Coding, RAG, and Agents | Agents, Vision, and Classification |
| Context window | 130k | 8k |
| Cheapest output | $2.15/1M tokens | $0.90/1M tokens |
| Provider routes | 7 tracked | 1 tracked |
| Shared benchmarks | MMLU PRO leader | 1 shared |
Decision tradeoffs
- DeepSeek R1 0528 holds a shared-benchmark lead on MMLU PRO, ahead by 13.7 points.
- DeepSeek R1 0528 has the larger context window for long prompts, retrieval packs, or transcript analysis.
- DeepSeek R1 0528 has broader tracked provider coverage for fallback and procurement flexibility.
- DeepSeek R1 0528 uniquely exposes Reasoning, Structured outputs, and Code execution in local model data.
- Local decision data tags DeepSeek R1 0528 for Coding, RAG, and Agents.
- Llama 3.3 70B has the lower cheapest tracked output price at $0.90/1M tokens.
- Llama 3.3 70B uniquely exposes Vision, Multimodal, and Function calling in local model data.
- Local decision data tags Llama 3.3 70B for Agents, Vision, and Classification.
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 3.3 70B
$945
Cheapest tracked route/tier: Fireworks AI
Estimated monthly gap: $7.50. 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 3.3 70B is $1.25/1M tokens lower on cheapest tracked output pricing before cache, batch, or negotiated discounts.
- Check replacement coverage for Reasoning, Structured outputs, and Code execution before moving production traffic.
- Llama 3.3 70B adds Vision, Multimodal, and Function calling in local capability data.
- Provider overlap exists on Fireworks AI; start route-level A/B tests there.
- DeepSeek R1 0528 is $1.25/1M tokens higher on cheapest tracked output pricing, so quality gains need to justify the spend.
- Check replacement coverage for Vision, Multimodal, and Function calling before moving production traffic.
- DeepSeek R1 0528 adds Reasoning, Structured outputs, and Code execution in local capability data.
Specs
| Specification | ||
|---|---|---|
| Released | 2025-05-28 | 2025-12-09 |
| 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 |
| Commercial use | Commercial use: permitted | Commercial use: conditional |
| Knowledge cutoff | - | 2024-12 |
Pricing and availability
| Pricing attribute | DeepSeek R1 0528 | Llama 3.3 70B |
|---|---|---|
| Input price | $0.50/1M tokens | $0.90/1M tokens |
| Output price | $2.15/1M tokens | $0.90/1M tokens |
| Providers |
Capabilities
| Capability | DeepSeek R1 0528 | Llama 3.3 70B |
|---|---|---|
| Vision | No | Yes |
| Multimodal | No | Yes |
| Reasoning | Yes | No |
| Function calling | No | Yes |
| Tool use | No | Yes |
| Structured outputs | Yes | No |
| Code execution | Yes | No |
| IDE integration | No | No |
| Computer use | No | No |
| Parallel agents | No | No |
Benchmarks
| Benchmark | DeepSeek R1 0528 | Llama 3.3 70B |
|---|---|---|
| MMLU PRO | 85.0 | 71.3 |
Deep dive
On shared benchmark coverage, MMLU PRO has DeepSeek R1 0528 at 85 and Llama 3.3 70B at 71.3, with DeepSeek R1 0528 ahead by 13.7 points. The largest visible gap is 13.7 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 vision: Llama 3.3 70B, multimodal input: Llama 3.3 70B, reasoning mode: DeepSeek R1 0528, function calling: Llama 3.3 70B, tool use: Llama 3.3 70B, structured outputs: DeepSeek R1 0528, and code execution: DeepSeek R1 0528. 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.
For cost, DeepSeek R1 0528 lists $0.50/1M input and $2.15/1M output tokens on the cheapest tracked provider, while Llama 3.3 70B lists $0.90/1M input and $0.90/1M output tokens on the cheapest tracked provider. A 70/30 input-output blend puts Llama 3.3 70B lower by about $0.09 per million blended tokens. Availability is 7 providers versus 1, so concentration risk also matters.
Choose DeepSeek R1 0528 when coding workflow support, larger context windows, and lower input-token cost are central to the workload. Choose Llama 3.3 70B when vision-heavy evaluation 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 3.3 70B?
DeepSeek R1 0528 supports 130k tokens, while Llama 3.3 70B 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 3.3 70B?
Llama 3.3 70B is cheaper on tracked token pricing. DeepSeek R1 0528 costs $0.50/1M input and $2.15/1M output tokens. Llama 3.3 70B costs $0.90/1M input and $0.90/1M output tokens. Provider discounts or batch pricing can still change the final bill.
Is DeepSeek R1 0528 or Llama 3.3 70B open source?
DeepSeek R1 0528 is listed under MIT. Llama 3.3 70B 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 R1 0528 or Llama 3.3 70B?
Llama 3.3 70B 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.
Which is better for multimodal input, DeepSeek R1 0528 or Llama 3.3 70B?
Llama 3.3 70B 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.
Where can I run DeepSeek R1 0528 and Llama 3.3 70B?
DeepSeek R1 0528 is available on Together AI, Fireworks AI, GCP Vertex AI, Novita AI, and OpenRouter. Llama 3.3 70B is available on Fireworks AI. Provider coverage can affect latency, region availability, compliance posture, and fallback options.
Continue comparing
Last reviewed: 2026-06-15. Data sourced from public model cards and provider documentation.