DeepSeek V3.2 vs Llama 4 Scout 17B 16E Instruct
At a Glance
| Compare |  DeepSeek V3.2DeepSeek | |
|---|---|---|
| Pricing and Limits | ||
| Input priceFrom · USD / 1M tokens | $0.26Deepinfra ↗ · Sep 22, 2026 | $0.10Deepinfra ↗ · Sep 22, 2026 |
| Output priceFrom · USD / 1M tokens | $0.38Deepinfra ↗ · Sep 22, 2026 | $0.30Deepinfra ↗ · Sep 22, 2026 |
| Context windowMaximum documented tokens | 164K | 10,000K |
| Model facts checked | Aug 28, 2026View model evidence → | Aug 28, 2026View model evidence → |
Token prices are the lowest available sourced USD rates; input and output may use different providers. Cost ranking estimates output spend on LiveBench, not a full request bill. Ranking methodology →
Available Benchmarks
| Benchmark | DeepSeek-V3.2 | Llama-4-Scout-17B-16E-Instruct |
|---|---|---|
| LMArena Text Arenatext-2026-09-13-d25aabda0010 · arena_rating · leader | 1,424.80100% of row best · rating · deepseek-v3.2; 95% CI [1421.27271719, 1428.32733406]; votes 46458; rank 96 | 1,279.2990% of row best · rating · llama-4-scout-17b-16e-instruct; 95% CI [1274.57681953, 1284.00026285]; votes 29740; rank 259 |
| Overall ResultCounted from the protocol-matched rows above | 1 benchmark winNo overall winner | 0 benchmark winsNo overall winner |
Third-party benchmark Only like-for-like primary-publisher results are shown; raw scores, relative scores, configuration, and token spend remain visible.
Side-by-Side Facts
| Field | DeepSeek-V3.2 | Llama-4-Scout-17B-16E-Instruct |
|---|---|---|
| Developer | DeepSeek | Meta |
| Family | Deepseek V3 2 | Llama 4 Scout 17b 16e Instruct |
| Model | DeepSeek-V3.2 | Llama-4-Scout-17B-16E-Instruct |
| Version | DeepSeek-V3.2 | Llama-4-Scout-17B-16E-Instruct |
| Lifecycle | active | active |
| Released | 2025-12-01 | 2025-04-05 |
| Knowledge cutoff | Unknown | Unknown |
| Input modalities | Text | Text, Image |
| Output modalities | Text | Text |
| Context window | 164K | 10,000K |
| Total parameters | 685.4B | 108.6B |
| Active parameters | Unknown | 17B |
| License | mit | other |
| Open weights | Yes | Yes |
| API available | Yes | Yes |
| Self-hostable | Yes | Yes |
| Provider access | Deepinfra (Standard), Hugging Face (Standard), Openrouter (Standard) | Deepinfra (Standard), Hugging Face (Standard), Openrouter (Standard), Together Ai (Standard) |
| Capabilities | chat, generation, reasoning | chat, generation, tools |
DeepSeek V3.2 Capabilities
Llama 4 Scout 17B 16E Instruct Capabilities
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DeepSeek-V3.2DeepSeek | vs | DeepSeek-V4.1-FlashDeepSeek | family variantstext |
DeepSeek-V3.2DeepSeek | vs | Grok 4.6xAI | cross-developer peerstext |
DeepSeek-V3.2DeepSeek | vs |  Qwen3.8-MaxQwen | cross-developer peerstext |
DeepSeek-V3.2DeepSeek | vs |  Kimi-K3Moonshot AI | cross-developer peerstext |
 MiniMax-M3MiniMax | vs | DeepSeek-V3.2DeepSeek | cross-developer peerstext |
DeepSeek-V3.2DeepSeek | vs |  GLM-5.3Z.ai | cross-developer peerstext |
DeepSeek-V3.2DeepSeek | vs |  Hy4 previewTencent | cross-developer peerstext |
Seed 2.1 ProByteDance Seed | vs | DeepSeek-V3.2DeepSeek | cross-developer peerstext |
DeepSeek-V3.2DeepSeek | vs |  Mistral Large 3Mistral AI | cross-developer peerstext |
Primary Evidence
Sources and Freshness
Questions
DeepSeek V3.2 vs Llama 4 Scout 17B 16E Instruct FAQs
Is DeepSeek V3.2 or Llama 4 Scout 17B 16E Instruct better for coding?+
This comparison does not currently contain a protocol-matched coding benchmark for both DeepSeek V3.2 and Llama 4 Scout 17B 16E Instruct, so Model Markets cannot name a coding leader from pricing, context size, or capability labels alone.
Which is cheaper, DeepSeek V3.2 or Llama 4 Scout 17B 16E Instruct?+
DeepSeek V3.2 is $0.26 and Llama 4 Scout 17B 16E Instruct is $0.10 per million tokens, so Llama 4 Scout 17B 16E Instruct is cheaper on this metric. DeepSeek V3.2 is $0.38 and Llama 4 Scout 17B 16E Instruct is $0.30 per million tokens, so Llama 4 Scout 17B 16E Instruct is cheaper on this metric.
Which has a larger context window, DeepSeek V3.2 or Llama 4 Scout 17B 16E Instruct?+
Llama 4 Scout 17B 16E Instruct has the larger sourced context window. DeepSeek V3.2 supports 164K and Llama 4 Scout 17B 16E Instruct supports 10,000K.
Which performs better in benchmarks, DeepSeek V3.2 or Llama 4 Scout 17B 16E Instruct?+
There is no overall benchmark winner: At least two independently verified, protocol-matched benchmarks are required for an overall winner.
Can DeepSeek V3.2 or Llama 4 Scout 17B 16E Instruct be self-hosted?+
Both models have the same recorded self-hosting status: supported. DeepSeek V3.2 is open weight; Llama 4 Scout 17B 16E Instruct is open weight.
Can DeepSeek V3.2 and Llama 4 Scout 17B 16E Instruct understand images?+
DeepSeek V3.2 is not documented with image input; Llama 4 Scout 17B 16E Instruct is documented with image input. This reflects supported input modalities, not vision quality.
Which can generate longer answers, DeepSeek V3.2 or Llama 4 Scout 17B 16E Instruct?+
Neither has a larger sourced maximum output. DeepSeek V3.2 is — and Llama 4 Scout 17B 16E Instruct is —.
Do DeepSeek V3.2 and Llama 4 Scout 17B 16E Instruct support reasoning and tool use?+
DeepSeek V3.2: reasoning. Llama 4 Scout 17B 16E Instruct: tool calling and image input. Feature support does not establish relative quality.
Which is available from more inference providers, DeepSeek V3.2 or Llama 4 Scout 17B 16E Instruct?+
DeepSeek V3.2 has 3 sourced provider routes; Llama 4 Scout 17B 16E Instruct has 4, so Llama 4 Scout 17B 16E Instruct has broader tracked availability.
Which offers better value, DeepSeek V3.2 or Llama 4 Scout 17B 16E Instruct?+
There is no universal value winner. Compare the input and output prices above with the matched benchmark result for your workload: cheaper tokens can be offset by different quality, token usage, latency, or provider availability.