Llama 3.3 70B Instruct vs Grok 4.20 Multi Agent
At a Glance
| Compare | ||
|---|---|---|
| Intelligence, Cost, and Efficiency | ||
| IntelligenceHigher is better · MM Intelligence v2.5 | UnrankedNot in the 46-model eligible cohort | #22 of 4663.4 score · 2/3 sources · provisional · missing LiveBench · full-core range 42.3–75.6 |
| Pricing and Limits | ||
| Input priceFrom · USD / 1M tokens | $0.10Openrouter ↗ · Sep 22, 2026 | $1.25Xai ↗ · Sep 3, 2026 |
| Output priceFrom · USD / 1M tokens | $0.32Openrouter ↗ · Sep 22, 2026 | $2.50Xai ↗ · Sep 3, 2026 |
| Context windowMaximum documented tokens | 131K | 1,000K |
| Model facts checked | Aug 28, 2026View model evidence → | Aug 29, 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 | Llama-3.3-70B-Instruct | Grok 4.20 Multi-Agent |
|---|---|---|
| LMArena Text Arenatext-2026-09-13-d25aabda0010 · arena_rating · leader | 1,273.9888% of row best · rating · llama-3.3-70b-instruct; 95% CI [1270.49383309, 1277.45726344]; votes 54412; rank 262 | 1,449.94100% of row best · rating · grok-4.20-multi-agent-beta-0309; 95% CI [1446.16660741, 1453.71198087]; votes 60777; rank 46 |
| Overall ResultCounted from the protocol-matched rows above | 0 benchmark winsNo overall winner | 1 benchmark winNo 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 | Llama-3.3-70B-Instruct | Grok 4.20 Multi-Agent |
|---|---|---|
| Developer | Meta | xAI |
| Family | Llama 3 3 70b Instruct | Grok 4 20 |
| Model | Llama-3.3-70B-Instruct | Grok 4.20 Multi-Agent |
| Version | Llama-3.3-70B-Instruct | Grok 4.20 Multi-Agent |
| Lifecycle | active | preview |
| Released | 2024-12-06 | Unknown |
| Knowledge cutoff | Unknown | Unknown |
| Input modalities | Text | Text, Image |
| Output modalities | Text | Text |
| Context window | 131K | 1,000K |
| Total parameters | 70.6B | Unknown |
| Active parameters | Unknown | Unknown |
| License | llama3.3 | Unknown |
| Open weights | Yes | No |
| API available | Yes | Yes |
| Self-hostable | Yes | No |
| Provider access | Hugging Face (Standard), Openrouter (Standard), Together Ai (Standard) | Xai (Standard) |
| Capabilities | chat, generation, tools | generation, reasoning, research, tools |
Llama 3.3 70B Instruct Capabilities
Grok 4.20 Multi Agent Capabilities
Related Comparisons
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|---|---|---|---|
| vs |  GPT-6 AstraOpenAI | cross-developer peerstext | |
Claude Fable 5.1Anthropic | vs | cross-developer peerstext | |
 Gemini 3.1 ProGoogle DeepMind | vs | cross-developer peerstext | |
 DeepSeek-V4.1-FlashDeepSeek | vs | cross-developer peerstext | |
| vs | Grok 4.6xAI | cross-developer peerstext | |
| vs |  Qwen3.8-MaxQwen | cross-developer peerstext | |
| vs |  Kimi-K3Moonshot AI | cross-developer peerstext | |
 MiniMax-M3MiniMax | vs | cross-developer peerstext | |
| vs |  GLM-5.3Z.ai | cross-developer peerstext | |
| vs |  Hy4 previewTencent | cross-developer peerstext | |
Seed 2.1 ProByteDance Seed | vs | cross-developer peerstext | |
| vs |  Mistral Large 3Mistral AI | cross-developer peerstext |
Primary Evidence
Sources and Freshness
Questions
Llama 3.3 70B Instruct vs Grok 4.20 Multi Agent FAQs
Is Llama 3.3 70B Instruct or Grok 4.20 Multi Agent better for coding?+
This comparison does not currently contain a protocol-matched coding benchmark for both Llama 3.3 70B Instruct and Grok 4.20 Multi Agent, so Model Markets cannot name a coding leader from pricing, context size, or capability labels alone.
Which is cheaper, Llama 3.3 70B Instruct or Grok 4.20 Multi Agent?+
Llama 3.3 70B Instruct is $0.10 and Grok 4.20 Multi Agent is $1.25 per million tokens, so Llama 3.3 70B Instruct is cheaper on this metric. Llama 3.3 70B Instruct is $0.32 and Grok 4.20 Multi Agent is $2.50 per million tokens, so Llama 3.3 70B Instruct is cheaper on this metric.
Which has a larger context window, Llama 3.3 70B Instruct or Grok 4.20 Multi Agent?+
Grok 4.20 Multi Agent has the larger sourced context window. Llama 3.3 70B Instruct supports 131K and Grok 4.20 Multi Agent supports 1,000K.
Which performs better in benchmarks, Llama 3.3 70B Instruct or Grok 4.20 Multi Agent?+
There is no overall benchmark winner: At least two independently verified, protocol-matched benchmarks are required for an overall winner.
Can Llama 3.3 70B Instruct or Grok 4.20 Multi Agent be self-hosted?+
Llama 3.3 70B Instruct is the only model in this pair currently marked as self-hostable. Llama 3.3 70B Instruct is open weight; Grok 4.20 Multi Agent is not marked open weight.
Can Llama 3.3 70B Instruct and Grok 4.20 Multi Agent understand images?+
Llama 3.3 70B Instruct is not documented with image input; Grok 4.20 Multi Agent is documented with image input. This reflects supported input modalities, not vision quality.
Which can generate longer answers, Llama 3.3 70B Instruct or Grok 4.20 Multi Agent?+
Neither has a larger sourced maximum output. Llama 3.3 70B Instruct is — and Grok 4.20 Multi Agent is —.
Do Llama 3.3 70B Instruct and Grok 4.20 Multi Agent support reasoning and tool use?+
Llama 3.3 70B Instruct: tool calling. Grok 4.20 Multi Agent: reasoning, tool calling, and image input. Feature support does not establish relative quality.
Which is available from more inference providers, Llama 3.3 70B Instruct or Grok 4.20 Multi Agent?+
Llama 3.3 70B Instruct has 3 sourced provider routes; Grok 4.20 Multi Agent has 1, so Llama 3.3 70B Instruct has broader tracked availability.
Which offers better value, Llama 3.3 70B Instruct or Grok 4.20 Multi Agent?+
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.