DeepSeek R1 vs Llama 3.2 11B Instruct
DeepSeek R1 (2025) and Llama 3.2 11B Instruct (2025) are frontier reasoning models from DeepSeek and AI at Meta. DeepSeek R1 ships a 128k-token context window, while Llama 3.2 11B Instruct ships a 128k-token context window. On pricing, DeepSeek R1 costs $0.10/1M input tokens versus $0.20/1M for the alternative. This comparison covers specs, pricing, API access, capabilities, benchmarks, input and output token costs, and production fit for coding and agent workloads.
DeepSeek R1 is ~100% cheaper at $0.10/1M; pay for Llama 3.2 11B Instruct only for vision-heavy evaluation.
Decision scorecard
Local evidence first| Signal | DeepSeek R1 | Llama 3.2 11B Instruct |
|---|---|---|
| Best for | reasoning-heavy apps and provider-routed production | multimodal apps |
| Decision fit | Coding, RAG, and Agents | RAG, Long context, and Vision |
| Context window | 128k | 128k |
| Cheapest output | $0.30/1M tokens | $0.27/1M tokens |
| Provider routes | 14 tracked | 1 tracked |
| Shared benchmarks | 0 rows | 0 rows |
Decision tradeoffs
- DeepSeek R1 has broader tracked provider coverage for fallback and procurement flexibility.
- DeepSeek R1 uniquely exposes Reasoning and Code execution in local model data.
- Local decision data tags DeepSeek R1 for Coding, RAG, and Agents.
- Llama 3.2 11B Instruct has the lower cheapest tracked output price at $0.27/1M tokens.
- Llama 3.2 11B Instruct uniquely exposes Vision and Multimodal in local model data.
- Local decision data tags Llama 3.2 11B Instruct for RAG, Long context, and Vision.
Monthly cost at traffic
Estimate token spend from the cheapest tracked input and output route or tier on this page.
DeepSeek R1
$155
Cheapest tracked route/tier: Bitdeer AI
Llama 3.2 11B Instruct
$228
Cheapest tracked route/tier: AWS Bedrock
Estimated monthly gap: $72.50. Batch, cache, alternate speed tiers, and negotiated pricing are excluded from this local estimate.
Switch friction
- Provider overlap exists on AWS Bedrock; start route-level A/B tests there.
- Llama 3.2 11B Instruct is $0.03/1M 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.
- Llama 3.2 11B Instruct adds Vision and Multimodal in local capability data.
- Provider overlap exists on AWS Bedrock; start route-level A/B tests there.
- DeepSeek R1 is $0.03/1M tokens higher on cheapest tracked output pricing, so quality gains need to justify the spend.
- Check replacement coverage for Vision and Multimodal before moving production traffic.
- DeepSeek R1 adds Reasoning and Code execution in local capability data.
Specs
| Specification | ||
|---|---|---|
| Released | 2025-01-20 | 2025-09-01 |
| Context window | 128k | 128k |
| Parameters | 671B, 37B Active | 11B |
| Architecture | 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 | 2023-12 |
Pricing and availability
| Pricing attribute | DeepSeek R1 | Llama 3.2 11B Instruct |
|---|---|---|
| Input price | $0.10/1M tokens | $0.20/1M tokens |
| Output price | $0.30/1M tokens | $0.27/1M tokens |
| Providers |
Capabilities
| Capability | DeepSeek R1 | Llama 3.2 11B Instruct |
|---|---|---|
| Vision | No | Yes |
| Multimodal | No | Yes |
| 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
No shared benchmark rows are currently sourced for this pair.
Deep dive
The capability footprint differs most on vision: Llama 3.2 11B Instruct, multimodal input: Llama 3.2 11B Instruct, reasoning mode: DeepSeek R1, and code execution: DeepSeek R1. 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 lists $0.10/1M input and $0.30/1M output tokens on the cheapest tracked provider, while Llama 3.2 11B Instruct lists $0.20/1M input and $0.27/1M output tokens on the cheapest tracked provider. A 70/30 input-output blend puts DeepSeek R1 lower by about $0.06 per million blended tokens. Availability is 14 providers versus 1, so concentration risk also matters.
Choose DeepSeek R1 when coding workflow support, lower input-token cost, and broader provider choice are central to the workload. Choose Llama 3.2 11B Instruct 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. This keeps the decision grounded in measurable tradeoffs instead of brand-level assumptions.
FAQ
Which has a larger context window, DeepSeek R1 or Llama 3.2 11B Instruct?
DeepSeek R1 supports 128k tokens, while Llama 3.2 11B 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 R1 or Llama 3.2 11B Instruct?
DeepSeek R1 is cheaper on tracked token pricing. DeepSeek R1 costs $0.10/1M input and $0.30/1M output tokens. Llama 3.2 11B Instruct costs $0.20/1M input and $0.27/1M output tokens. Provider discounts or batch pricing can still change the final bill.
Is DeepSeek R1 or Llama 3.2 11B Instruct open source?
DeepSeek R1 is listed under MIT. Llama 3.2 11B 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 vision, DeepSeek R1 or Llama 3.2 11B Instruct?
Llama 3.2 11B Instruct 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 or Llama 3.2 11B Instruct?
Llama 3.2 11B Instruct 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 and Llama 3.2 11B Instruct?
DeepSeek R1 is available on DeepSeek Platform, OpenRouter, Together AI, Fireworks AI, and NVIDIA NIM. Llama 3.2 11B Instruct is available on AWS Bedrock. Provider coverage can affect latency, region availability, compliance posture, and fallback options.
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Last reviewed: 2026-06-04. Data sourced from public model cards and provider documentation.