DeepSeek R1 vs Llama 3.3 70B Instruct
At a Glance
| Compare |  DeepSeek R1DeepSeek | |
|---|---|---|
| Pricing and Limits | ||
| Input priceFrom · USD / 1M tokens | $0.70Openrouter ↗ · Aug 28, 2026 | $0.10Openrouter ↗ · Sep 23, 2026 |
| Output priceFrom · USD / 1M tokens | $2.50Openrouter ↗ · Aug 28, 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-R1 | Llama-3.3-70B-Instruct |
|---|---|---|
| LMArena Text Arenatext-2026-09-13-d25aabda0010 · arena_rating · leader | 1,372.60100% of row best · rating · deepseek-r1; 95% CI [1367.75270193, 1377.44238946]; votes 18524; rank 168 | 1,273.9893% 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-R1 | Llama-3.3-70B-Instruct |
|---|---|---|
| Developer | DeepSeek | Meta |
| Family | Deepseek R1 | Llama 3 3 70b Instruct |
| Model | DeepSeek-R1 | Llama-3.3-70B-Instruct |
| Version | DeepSeek-R1 | Llama-3.3-70B-Instruct |
| Lifecycle | active | active |
| Released | 2025-01-20 | 2024-12-06 |
| Knowledge cutoff | Unknown | Unknown |
| Input modalities | Text | Text |
| Output modalities | Text | Text |
| Context window | 164K | 131K |
| Total parameters | 684.5B | 70.6B |
| Active parameters | 37B | Unknown |
| License | mit | llama3.3 |
| Open weights | Yes | Yes |
| API available | Yes | Yes |
| Self-hostable | Yes | Yes |
| Provider access | Hugging Face (Standard), Openrouter (Standard) | Hugging Face (Standard), Openrouter (Standard), Together Ai (Standard) |
| Capabilities | chat, generation, reasoning | chat, generation, tools |
DeepSeek R1 Capabilities
Llama 3.3 70B Instruct Capabilities
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Primary Evidence
Sources and Freshness
Questions
DeepSeek R1 vs Llama 3.3 70B Instruct FAQs
Is DeepSeek R1 or Llama 3.3 70B Instruct better for coding?+
This comparison does not currently contain a protocol-matched coding benchmark for both DeepSeek R1 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 R1 or Llama 3.3 70B Instruct?+
DeepSeek R1 is $0.70 and Llama 3.3 70B Instruct is $0.10 per million tokens, so Llama 3.3 70B Instruct is cheaper on this metric. DeepSeek R1 is $2.50 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 R1 or Llama 3.3 70B Instruct?+
DeepSeek R1 has the larger sourced context window. DeepSeek R1 supports 164K and Llama 3.3 70B Instruct supports 131K.
Which performs better in benchmarks, DeepSeek R1 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 R1 or Llama 3.3 70B Instruct be self-hosted?+
Both models have the same recorded self-hosting status: supported. DeepSeek R1 is open weight; Llama 3.3 70B Instruct is open weight.
Can DeepSeek R1 and Llama 3.3 70B Instruct understand images?+
DeepSeek R1 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 R1 or Llama 3.3 70B Instruct?+
Neither has a larger sourced maximum output. DeepSeek R1 is 33K and Llama 3.3 70B Instruct is —.
Do DeepSeek R1 and Llama 3.3 70B Instruct support reasoning and tool use?+
DeepSeek R1: reasoning. Llama 3.3 70B Instruct: tool calling. Feature support does not establish relative quality.
Which is available from more inference providers, DeepSeek R1 or Llama 3.3 70B Instruct?+
DeepSeek R1 has 2 sourced provider routes; Llama 3.3 70B Instruct has 3, so Llama 3.3 70B Instruct has broader tracked availability.
Which offers better value, DeepSeek R1 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.