Compare AI models
| Specifications | ||
ParametersThe learned values that shape how a model responds. B means billion and T means trillion. For mixture-of-experts models, the total count is larger than the number active for each token. Parameter count alone does not measure quality. | 8B/70B | — |
Context windowHow much information the model can work with in one request, measured in tokens — pieces of words or other data. This includes your question, attachments, conversation and reply. Limits can vary by model variant and provider. | 8k | 1.05M |
| API pricingUSD per 1M tokens · lower wins | ||
Input priceWhat you pay for everything you send the model — your question, plus any documents or earlier conversation you include with it. | — | $30.00 |
Output priceWhat you pay for the text the model writes back. It is normally the dearer half: producing an answer costs more than reading one. | — | $180.00 |
Cheapest inputLowest input rate across every provider on OpenRouter, the lab included. The cheapest endpoint may run a quantised build or a shorter context — see "Available from" on the model page. | — | $15.00OpenAI |
Cheapest outputLowest output rate across every provider on OpenRouter, the lab included. May come from a different provider than the cheapest input. | — | $90.00OpenAI |
| — | $15,000OpenAI list price | |
| These models have no shared benchmark scores. | ||
BullshitBench v2Nonsense detection — Given a confidently-worded but nonsensical prompt, does the AI spot that it makes no sense and push back — instead of playing along and inventing an answer? The score is how often it clearly called out the nonsense. Higher is better. | — | 36% |
Next.js EvalsNext.js coding — Vercel's open eval of how well AI coding agents build and migrate real Next.js apps — measured as the share of tasks the agent completes successfully. Higher is better. | — | 65% |
BrowseCompWeb browsing — Can the AI browse the web and track down hard-to-find answers? Higher is better. | — | 90.1% |
Humanity's Last Exam · with toolsMultidisciplinary reasoning — Humanity's Last Exam — extremely hard expert questions across many subjects. “With tools” means the AI is allowed to search the web or run code while answering. Higher is better. | — | 57.2% |
ARC-AGI-2Abstract reasoning — Puzzle-style tests of abstract reasoning and pattern-finding — the kind of thing people find easy but AIs often struggle with. Higher is better. | — | 84.2% |
FrontierMath · Tier 1–3Advanced math — Very hard, research-level math problems. Tiers 1–3 are the (still extremely difficult) lower tiers. Higher is better. | — | 52.4% |
FrontierMath · Tier 4Advanced math — Very hard, research-level math problems. Tier 4 is the hardest — close to what professional research mathematicians tackle. Higher is better. | — | 39.6% |
GDPval (win/tie rate)Knowledge work — How often the AI's work matches or beats a human expert's on real knowledge-work tasks. Higher is better. | — | 82.3% |
| Overview | ||
| Company | Meta | OpenAI |
| Release date | Apr 18 2024 | Apr 23 2026 |
| Access | Open Weight | Closed |
| Model details | View model | View model |
Other comparisons
LLaMA 3 (8B/70B)vsClaude Haiku 5.5GPT-5.5-ProvsClaude Haiku 5.5LLaMA 3 (8B/70B)vsGemini 4 ArgonGPT-5.5-ProvsGemini 4 ArgonLLaMA 3 (8B/70B)vsGrok 4.7GPT-5.5-ProvsGrok 4.7LLaMA 3 (8B/70B)vsDeepSeek-V4.1-Flash-1017GPT-5.5-ProvsDeepSeek-V4.1-Flash-1017LLaMA 3 (8B/70B)vsMistral Large 4GPT-5.5-ProvsMistral Large 4LLaMA 3 (8B/70B)vsKimi K3GPT-5.5-ProvsKimi K3Frequently asked questions
LLaMA 3 (8B/70B) and GPT-5.5-Pro don't publish scores on any of the same benchmarks, so there's no direct head-to-head comparison. Only GPT-5.5-Pro has a verified first-party API price: $30.00 per million input tokens and $180.00 per million output tokens. No pay-as-you-go API rate is tracked for LLaMA 3 (8B/70B). LLaMA 3 (8B/70B) shipped 735 days before GPT-5.5-Pro, so benchmark comparisons should account for the intervening progress.
Context windows are 8k (LLaMA 3 (8B/70B)) vs 1.05M (GPT-5.5-Pro). LLaMA 3 (8B/70B) is open weight, while GPT-5.5-Pro is closed.
Direct benchmark comparisons are unavailable — LLaMA 3 (8B/70B) and GPT-5.5-Pro don't publish scores on any of the same benchmarks.