DeepSeek V3 vs Llama 4 Scout 17B Instruct
DeepSeek V3 (2024) and Llama 4 Scout 17B Instruct (2026) are compact production models from DeepSeek and AI at Meta. DeepSeek V3 ships a 64k-token context window, while Llama 4 Scout 17B Instruct ships a not-yet-sourced context window. On Chatbot Arena, DeepSeek V3 leads by 7 pts. On pricing, DeepSeek V3 costs $0.1/1M input tokens versus $0.17/1M for the alternative. This comparison covers specs, pricing, capabilities, benchmarks, provider availability, and production fit.
DeepSeek V3 is ~70% cheaper at $0.1/1M; pay for Llama 4 Scout 17B Instruct only for provider fit.
Specs
| Specification | ||
|---|---|---|
| Released | 2024-12-26 | 2026-01-01 |
| Context window | 64k | — |
| Parameters | 671B | — |
| Architecture | mixture of experts | - |
| License | Open Source | Proprietary |
| Knowledge cutoff | 2024-04 | - |
Pricing and availability
| Pricing attribute | DeepSeek V3 | Llama 4 Scout 17B Instruct |
|---|---|---|
| Input price | $0.1/1M tokens | $0.17/1M tokens |
| Output price | $0.3/1M tokens | $0.66/1M tokens |
| Providers |
Capabilities
| Capability | DeepSeek V3 | Llama 4 Scout 17B Instruct |
|---|---|---|
| Vision | No | No |
| Multimodal | No | Yes |
| Reasoning | No | No |
| Function calling | Yes | No |
| Tool use | Yes | No |
| Structured outputs | Yes | Yes |
| Code execution | No | No |
Benchmarks
| Benchmark | DeepSeek V3 | Llama 4 Scout 17B Instruct |
|---|---|---|
| Chatbot Arena | 1302.0 | 1295.0 |
Deep dive
On shared benchmark coverage, Chatbot Arena has DeepSeek V3 at 1302 and Llama 4 Scout 17B Instruct at 1295, with DeepSeek V3 ahead by 7 points. The largest visible gap is 7 points on Chatbot Arena, 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 multimodal input: Llama 4 Scout 17B Instruct, function calling: DeepSeek V3, and tool use: DeepSeek V3. 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 V3 lists $0.1/1M input and $0.3/1M output tokens, while Llama 4 Scout 17B Instruct lists $0.17/1M input and $0.66/1M output tokens on the cheapest tracked provider. A 70/30 input-output blend puts DeepSeek V3 lower by about $0.16 per million blended tokens. Availability is 12 providers versus 1, so concentration risk also matters.
Choose DeepSeek V3 when provider fit, lower input-token cost, and broader provider choice are central to the workload. Choose Llama 4 Scout 17B Instruct when provider fit are more important. For production, rerun your own prompts through the exact provider, region, and tool stack you plan to ship.
FAQ
Which is cheaper, DeepSeek V3 or Llama 4 Scout 17B Instruct?
DeepSeek V3 is cheaper on tracked token pricing. DeepSeek V3 costs $0.1/1M input and $0.3/1M output tokens. Llama 4 Scout 17B Instruct costs $0.17/1M input and $0.66/1M output tokens. Provider discounts or batch pricing can still change the final bill.
Is DeepSeek V3 or Llama 4 Scout 17B Instruct open source?
DeepSeek V3 is listed under Open Source. Llama 4 Scout 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 multimodal input, DeepSeek V3 or Llama 4 Scout 17B Instruct?
Llama 4 Scout 17B 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 function calling, DeepSeek V3 or Llama 4 Scout 17B Instruct?
DeepSeek V3 has the clearer documented function calling signal in this comparison. If function calling is mission-critical, validate it against the provider endpoint because model-level support and API-level exposure can differ.
Which is better for tool use, DeepSeek V3 or Llama 4 Scout 17B Instruct?
DeepSeek V3 has the clearer documented tool use signal in this comparison. If tool use is mission-critical, validate it against the provider endpoint because model-level support and API-level exposure can differ.
Where can I run DeepSeek V3 and Llama 4 Scout 17B Instruct?
DeepSeek V3 is available on DeepInfra, Fireworks AI, DeepSeek Platform, Microsoft Foundry, and OpenRouter. Llama 4 Scout 17B Instruct is available on AWS Bedrock. Provider coverage can affect latency, region availability, compliance posture, and fallback options.
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Last reviewed: 2026-05-11. Data sourced from public model cards and provider documentation.