DeepSeek V3.2 vs Llama 3.3 70B Instruct
At a Glance
| Compare |  DeepSeek V3.2DeepSeek | |
|---|---|---|
| Pricing and Limits | ||
| Input priceFrom · USD / 1M tokens | $0.26Deepinfra ↗ · Sep 23, 2026 | $0.10Openrouter ↗ · Sep 23, 2026 |
| Output priceFrom · USD / 1M tokens | $0.38Deepinfra ↗ · Sep 23, 2026 | $0.32Openrouter ↗ · Sep 23, 2026 |
| Context windowMaximum documented tokens | 164K | 131K |
| 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-3.3-70B-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 | 1,273.9889% of row best · rating · llama-3.3-70b-instruct; 95% CI [1270.49383309, 1277.45726344]; votes 54412; rank 262 |
| 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-3.3-70B-Instruct |
|---|---|---|
| Developer | DeepSeek | Meta |
| Family | Deepseek V3 2 | Llama 3 3 70b Instruct |
| Model | DeepSeek-V3.2 | Llama-3.3-70B-Instruct |
| Version | DeepSeek-V3.2 | Llama-3.3-70B-Instruct |
| Lifecycle | active | active |
| Released | 2025-12-01 | 2024-12-06 |
| Knowledge cutoff | Unknown | Unknown |
| Input modalities | Text | Text |
| Output modalities | Text | Text |
| Context window | 164K | 131K |
| Total parameters | 685.4B | 70.6B |
| Active parameters | Unknown | Unknown |
| License | mit | llama3.3 |
| Open weights | Yes | Yes |
| API available | Yes | Yes |
| Self-hostable | Yes | Yes |
| Provider access | Deepinfra (Standard), Hugging Face (Standard), Openrouter (Standard) | Hugging Face (Standard), Openrouter (Standard), Together Ai (Standard) |
| Capabilities | chat, generation, reasoning | chat, generation, tools |
DeepSeek V3.2 Capabilities
Llama 3.3 70B 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 3.3 70B Instruct FAQs
Is DeepSeek V3.2 or Llama 3.3 70B Instruct better for coding?+
This comparison does not currently contain a protocol-matched coding benchmark for both DeepSeek V3.2 and Llama 3.3 70B 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 3.3 70B Instruct?+
DeepSeek V3.2 is $0.26 and Llama 3.3 70B Instruct is $0.10 per million tokens, so Llama 3.3 70B Instruct is cheaper on this metric. DeepSeek V3.2 is $0.38 and Llama 3.3 70B Instruct is $0.32 per million tokens, so Llama 3.3 70B Instruct is cheaper on this metric.
Which has a larger context window, DeepSeek V3.2 or Llama 3.3 70B Instruct?+
DeepSeek V3.2 has the larger sourced context window. DeepSeek V3.2 supports 164K and Llama 3.3 70B Instruct supports 131K.
Which performs better in benchmarks, DeepSeek V3.2 or Llama 3.3 70B 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 3.3 70B Instruct be self-hosted?+
Both models have the same recorded self-hosting status: supported. DeepSeek V3.2 is open weight; Llama 3.3 70B Instruct is open weight.
Can DeepSeek V3.2 and Llama 3.3 70B Instruct understand images?+
DeepSeek V3.2 is not documented with image input; Llama 3.3 70B Instruct is not documented with image input. This reflects supported input modalities, not vision quality.
Which can generate longer answers, DeepSeek V3.2 or Llama 3.3 70B Instruct?+
Neither has a larger sourced maximum output. DeepSeek V3.2 is — and Llama 3.3 70B Instruct is —.
Do DeepSeek V3.2 and Llama 3.3 70B Instruct support reasoning and tool use?+
DeepSeek V3.2: reasoning. Llama 3.3 70B Instruct: tool calling. Feature support does not establish relative quality.
Which is available from more inference providers, DeepSeek V3.2 or Llama 3.3 70B Instruct?+
DeepSeek V3.2 has 3 sourced provider routes; Llama 3.3 70B Instruct has 3, a tie.
Which offers better value, DeepSeek V3.2 or Llama 3.3 70B 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.