DeepSeek V3.1 vs Llama 4 Maverick 17B Instruct
DeepSeek V3.1 (2026) and Llama 4 Maverick 17B Instruct (2026) are compact production models from DeepSeek and AI at Meta. DeepSeek V3.1 ships a 64K-token context window, while Llama 4 Maverick 17B Instruct ships a not-yet-sourced context window. On pricing, Llama 4 Maverick 17B Instruct costs $0.24/1M input tokens versus $0.56/1M for the alternative. This comparison covers specs, pricing, capabilities, benchmarks, provider availability, and production fit.
Llama 4 Maverick 17B Instruct is ~133% cheaper at $0.24/1M; pay for DeepSeek V3.1 only for coding workflow support.
Specs
| Specification | ||
|---|---|---|
| Released | 2026-03-01 | 2026-01-01 |
| Context window | 64K | — |
| Parameters | — | — |
| Architecture | mixture of experts | - |
| License | Open Source | Proprietary |
| Knowledge cutoff | - | - |
Pricing and availability
| Pricing attribute | DeepSeek V3.1 | Llama 4 Maverick 17B Instruct |
|---|---|---|
| Input price | $0.56/1M tokens | $0.24/1M tokens |
| Output price | $1.68/1M tokens | $0.97/1M tokens |
| Providers |
Capabilities
| Capability | DeepSeek V3.1 | Llama 4 Maverick 17B Instruct |
|---|---|---|
| Vision | Yes | No |
| Multimodal | Yes | Yes |
| Reasoning | No | No |
| Function calling | No | No |
| Tool use | No | No |
| Structured outputs | Yes | Yes |
| Code execution | Yes | No |
Benchmarks
No shared benchmark rows are currently sourced for this pair.
Deep dive
The capability footprint differs most on vision: DeepSeek V3.1 and code execution: DeepSeek V3.1. Both models share multimodal input and 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 V3.1 lists $0.56/1M input and $1.68/1M output tokens, while Llama 4 Maverick 17B Instruct lists $0.24/1M input and $0.97/1M output tokens on the cheapest tracked provider. A 70/30 input-output blend puts Llama 4 Maverick 17B Instruct lower by about $0.44 per million blended tokens. Availability is 6 providers versus 1, so concentration risk also matters.
Choose DeepSeek V3.1 when coding workflow support and broader provider choice are central to the workload. Choose Llama 4 Maverick 17B Instruct when provider fit and lower input-token cost 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 is cheaper, DeepSeek V3.1 or Llama 4 Maverick 17B Instruct?
Llama 4 Maverick 17B Instruct is cheaper on tracked token pricing. DeepSeek V3.1 costs $0.56/1M input and $1.68/1M output tokens. Llama 4 Maverick 17B Instruct costs $0.24/1M input and $0.97/1M output tokens. Provider discounts or batch pricing can still change the final bill.
Is DeepSeek V3.1 or Llama 4 Maverick 17B Instruct open source?
DeepSeek V3.1 is listed under Open Source. Llama 4 Maverick 17B Instruct is listed under Proprietary. 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 V3.1 or Llama 4 Maverick 17B Instruct?
DeepSeek V3.1 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. Use this as a quick comparison signal, then confirm the provider-specific limits before committing to production.
Which is better for multimodal input, DeepSeek V3.1 or Llama 4 Maverick 17B Instruct?
Both DeepSeek V3.1 and Llama 4 Maverick 17B Instruct expose multimodal input. The better choice depends on benchmark fit, context budget, pricing, and whether your provider route exposes the same capability surface.
Which is better for structured outputs, DeepSeek V3.1 or Llama 4 Maverick 17B Instruct?
Both DeepSeek V3.1 and Llama 4 Maverick 17B 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 V3.1 and Llama 4 Maverick 17B Instruct?
DeepSeek V3.1 is available on Microsoft Foundry, Fireworks AI, NVIDIA NIM, Together AI, and AWS Bedrock. Llama 4 Maverick 17B Instruct is available on AWS Bedrock. Provider coverage can affect latency, region availability, compliance posture, and fallback options.
Continue comparing
Last reviewed: 2026-05-11. Data sourced from public model cards and provider documentation.