Llama 3.3 70B Instruct vs GPT-5.2
At a Glance
| Compare |  GPT-5.2OpenAI | |
|---|---|---|
| Intelligence, Cost, and Efficiency | ||
| IntelligenceHigher is better · MM Intelligence v2.5 | UnrankedNot in the 46-model eligible cohort | #33 of 4649.3 score · 3/3 sources · complete |
| CostLower is better · Published-token output estimate | UnrankedNot in the 44-model eligible cohort | #28 of 44$0.161 per LiveBench case |
| EfficiencyHigher is better · MM Efficiency v1.5 | UnrankedNot in the 38-model eligible cohort | #34 of 3844.0 score · 3/3 sources · complete |
| Pricing and Limits | ||
| Input priceFrom · USD / 1M tokens | $0.10Openrouter ↗ · Sep 23, 2026 | $1.75Openai ↗ · Sep 3, 2026 |
| Output priceFrom · USD / 1M tokens | $0.32Openrouter ↗ · Sep 23, 2026 | $14.00Openai ↗ · Sep 3, 2026 |
| Context windowMaximum documented tokens | 131K | 400K |
| Model facts checked | Aug 28, 2026View model evidence → | Sep 3, 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 | GPT-5.2 |
|---|---|---|
| Berkeley Function Calling Leaderboardv4-ede5081a24bc · overall_accuracy · leader | 31.9070% of row best · percent · Llama-3.3-70B-Instruct (FC) | 45.27100% of row best · percent · GPT-5.2-2025-12-11 (Prompt) |
| LMArena Text Arenatext-2026-09-13-d25aabda0010 · arena_rating · leader | 1,273.9890% of row best · rating · llama-3.3-70b-instruct; 95% CI [1270.49383309, 1277.45726344]; votes 54412; rank 262 | 1,412.43100% of row best · rating · gpt-5.2; 95% CI [1409.21136225, 1415.65317114]; votes 78967; rank 125 |
| Overall ResultCounted from the protocol-matched rows above | 0 benchmark wins | 2 benchmark winsOverall lead |
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 | GPT-5.2 |
|---|---|---|
| Developer | Meta | OpenAI |
| Family | Llama 3 3 70b Instruct | Gpt 5 2 |
| Model | Llama-3.3-70B-Instruct | GPT-5.2 |
| Version | Llama-3.3-70B-Instruct | GPT-5.2 |
| Lifecycle | active | active |
| Released | 2024-12-06 | 2025-12-11 |
| Knowledge cutoff | Unknown | 2025-08-31 |
| Input modalities | Text | Text, Image |
| Output modalities | Text | Text |
| Context window | 131K | 400K |
| 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) | Openai (Standard), Openrouter (Standard) |
| Capabilities | chat, generation, tools | chat, generation, reasoning, structured_outputs, tools |
Llama 3.3 70B Instruct Capabilities
GPT-5.2 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 GPT-5.2 FAQs
Is Llama 3.3 70B Instruct or GPT-5.2 better for coding?+
This comparison does not currently contain a protocol-matched coding benchmark for both Llama 3.3 70B Instruct and GPT-5.2, 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 GPT-5.2?+
Llama 3.3 70B Instruct is $0.10 and GPT-5.2 is $1.75 per million tokens, so Llama 3.3 70B Instruct is cheaper on this metric. Llama 3.3 70B Instruct is $0.32 and GPT-5.2 is $14.00 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 GPT-5.2?+
GPT-5.2 has the larger sourced context window. Llama 3.3 70B Instruct supports 131K and GPT-5.2 supports 400K.
Which performs better in benchmarks, Llama 3.3 70B Instruct or GPT-5.2?+
GPT-5.2 leads the current overall benchmark count. The result uses 2 protocol-matched benchmarks from 2 publishers; it is not a universal quality score.
Can Llama 3.3 70B Instruct or GPT-5.2 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; GPT-5.2 is not marked open weight.
Can Llama 3.3 70B Instruct and GPT-5.2 understand images?+
Llama 3.3 70B Instruct is not documented with image input; GPT-5.2 is documented with image input. This reflects supported input modalities, not vision quality.
Which can generate longer answers, Llama 3.3 70B Instruct or GPT-5.2?+
Neither has a larger sourced maximum output. Llama 3.3 70B Instruct is — and GPT-5.2 is 128K.
Do Llama 3.3 70B Instruct and GPT-5.2 support reasoning and tool use?+
Llama 3.3 70B Instruct: tool calling. GPT-5.2: 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 GPT-5.2?+
Llama 3.3 70B Instruct has 3 sourced provider routes; GPT-5.2 has 2, so Llama 3.3 70B Instruct has broader tracked availability.
Which offers better value, Llama 3.3 70B Instruct or GPT-5.2?+
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.