DeepSeek R1 Lite vs Llama 3.2 90B Instruct
DeepSeek R1 Lite (2024) and Llama 3.2 90B Instruct (2025) are frontier reasoning models from DeepSeek and AI at Meta. DeepSeek R1 Lite ships a 128k-token context window, while Llama 3.2 90B Instruct ships a 128k-token context window. This comparison covers specs, pricing, API access, capabilities, benchmarks, input and output token costs, and production fit for coding and agent workloads.
Llama 3.2 90B Instruct is safer overall; choose DeepSeek R1 Lite when reasoning depth matters.
Decision scorecard
Local evidence first| Signal | DeepSeek R1 Lite | Llama 3.2 90B Instruct |
|---|---|---|
| Best for | reasoning-heavy apps | multimodal apps |
| Decision fit | Long context | RAG, Long context, and Vision |
| Context window | 128k | 128k |
| Cheapest output | - | $1.80/1M tokens |
| Provider routes | 0 tracked | 1 tracked |
| Shared benchmarks | 0 rows | 0 rows |
Decision tradeoffs
- DeepSeek R1 Lite uniquely exposes Reasoning in local model data.
- Local decision data tags DeepSeek R1 Lite for Long context.
- Llama 3.2 90B Instruct has broader tracked provider coverage for fallback and procurement flexibility.
- Llama 3.2 90B Instruct uniquely exposes Vision, Multimodal, and Structured outputs in local model data.
- Local decision data tags Llama 3.2 90B 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 Lite
Unavailable
No complete token price in local provider data
Llama 3.2 90B Instruct
$1,530
Cheapest tracked route/tier: AWS Bedrock
Cost delta unavailable until both models have sourced input and output token prices.
Switch friction
- No overlapping tracked provider route is sourced for DeepSeek R1 Lite and Llama 3.2 90B Instruct; plan for SDK, billing, or endpoint changes.
- Check replacement coverage for Reasoning before moving production traffic.
- Llama 3.2 90B Instruct adds Vision, Multimodal, and Structured outputs in local capability data.
- No overlapping tracked provider route is sourced for Llama 3.2 90B Instruct and DeepSeek R1 Lite; plan for SDK, billing, or endpoint changes.
- Check replacement coverage for Vision, Multimodal, and Structured outputs before moving production traffic.
- DeepSeek R1 Lite adds Reasoning in local capability data.
Specs
| Specification | ||
|---|---|---|
| Released | 2024-11-21 | 2025-09-01 |
| Context window | 128k | 128k |
| Parameters | — | 90B |
| 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 |
Pricing and availability
| Pricing attribute | DeepSeek R1 Lite | Llama 3.2 90B Instruct |
|---|---|---|
| Input price | - | $1.35/1M tokens |
| Output price | - | $1.80/1M tokens |
| Providers | - |
Capabilities
| Capability | DeepSeek R1 Lite | Llama 3.2 90B Instruct |
|---|---|---|
| Vision | No | Yes |
| Multimodal | No | Yes |
| Reasoning | Yes | No |
| Function calling | No | No |
| Tool use | No | No |
| Structured outputs | No | Yes |
| Code execution | No | 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 90B Instruct, multimodal input: Llama 3.2 90B Instruct, reasoning mode: DeepSeek R1 Lite, and structured outputs: Llama 3.2 90B Instruct. 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.
Pricing coverage is uneven: DeepSeek R1 Lite has no token price sourced yet and Llama 3.2 90B Instruct has $1.35/1M input tokens. Provider availability is 0 tracked routes versus 1. Treat unknown pricing as an integration gap, then verify the route you will actually call before estimating production spend.
Choose DeepSeek R1 Lite when reasoning depth are central to the workload. Choose Llama 3.2 90B Instruct when vision-heavy evaluation 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. This keeps the decision grounded in measurable tradeoffs instead of brand-level assumptions. It also helps separate model capability from provider packaging, which can change cost and latency.
FAQ
Which has a larger context window, DeepSeek R1 Lite or Llama 3.2 90B Instruct?
DeepSeek R1 Lite supports 128k tokens, while Llama 3.2 90B Instruct supports 128k tokens. That gap matters most for long documents, large codebases, retrieval-heavy agents, and conversations where earlier context must remain visible.
Is DeepSeek R1 Lite or Llama 3.2 90B Instruct open source?
DeepSeek R1 Lite is listed under MIT. Llama 3.2 90B 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 Lite or Llama 3.2 90B Instruct?
Llama 3.2 90B 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 Lite or Llama 3.2 90B Instruct?
Llama 3.2 90B 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.
Which is better for reasoning mode, DeepSeek R1 Lite or Llama 3.2 90B Instruct?
DeepSeek R1 Lite 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.
Where can I run DeepSeek R1 Lite and Llama 3.2 90B Instruct?
DeepSeek R1 Lite is available on the tracked providers still being sourced. Llama 3.2 90B 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.