Updated February 2026
Frontier AI Models Intelligence Hub
Benchmarks, pricing, context windows, and capabilities for every frontier model worth tracking. Data validated against official sources and independent benchmarks.
Frontier Models (February 2026)
Sorted by reasoning capability. Pricing per 1M tokens.
Anthropic • Released Feb 5, 2026
#1 ARC-AGI-2 (68.8%), #1 Terminal-Bench (65.4%)
Context
1M (beta)
Output
128K
Price In/Out
$5/$25
New flagship. Adaptive thinking replaces budget_tokens. 67% price cut from Opus 4.5.
GPT-5.2 Pro
OpenAI • Released Jan 2026
First 90% ARC-AGI-1, multimodal w/ audio
Context
196K
Output
64K
Price In/Out
$10/$30
Native audio modality. Strong general-purpose performance.
Gemini 3 Pro
Google DeepMind • Released Dec 2025
Best multimodal (81% MMMU-Pro), 2M context
Context
2M
Output
64K
Price In/Out
$7/$21
Widest modality support: text, vision, audio, video. 2M native context.
Grok 4.1
xAI • Released Nov 2025
#1 LMArena (1483 Elo), 2M context
Context
2M
Output
64K
Price In/Out
$3/$15
Top LMArena Elo. Competitive pricing with long context.
Claude Opus 4.5
Anthropic • Released Nov 2025
Best coding at launch (80.9% SWE-bench)
Context
200K
Output
64K
Price In/Out
$5/$25
Previous flagship. Still available, superseded by Opus 4.6.
Llama 4 Maverick
Meta • Released Dec 2025
Open-weight MoE (400B/17B active)
Context
1M
Output
32K
Price In/Out
Open
Open-weight. 400B total, 17B active per token. Runs on single H100.
DeepSeek R1
DeepSeek • Released Jan 2025
Open-source reasoning champion, MIT license
Context
128K
Output
32K
Price In/Out
$0.55/$2.19
Most cost-effective reasoning model. Open-source under MIT license.
Benchmark Comparison
Head-to-head scores where data is available. Higher is better.
| Benchmark | What It Tests | Opus 4.6 | GPT-5.2 | Gemini 3 | Opus 4.5 |
|---|---|---|---|---|---|
| ARC-AGI-2 | Abstract reasoning | 68.8% | 54.2% | 45.1% | 37.6% |
| Terminal-Bench 2.0 | Agentic coding | 65.4% | — | — | 59.8% |
| OSWorld | Computer use | 72.7% | — | — | 66.3% |
| MMMU-Pro | Multimodal understanding | — | — | 81% | — |
| BigLaw Bench | Legal reasoning | 90.2% | — | — | — |
| MRCR v2 (1M) | Long-context retrieval | 76% | — | — | — |
Sources: Official vendor announcements, ARC Prize Foundation, SWE-bench project. Last validated February 6, 2026.
Pricing Matrix (per 1M tokens)
Input/output pricing for standard API access. Cached and batch pricing varies.
| Model | Input | Output | Context | Cost per 10K conversation |
|---|---|---|---|---|
| Claude Opus 4.6 | $5.00 | $25.00 | 1M (beta) | $0.15 |
| GPT-5.2 Pro | $10.00 | $30.00 | 196K | $0.20 |
| Gemini 3 Pro | $7.00 | $21.00 | 2M | $0.14 |
| Grok 4.1 | $3.00 | $15.00 | 2M | $0.09 |
| Claude Opus 4.5 | $5.00 | $25.00 | 200K | $0.15 |
| DeepSeek R1 | $0.55 | $2.19 | 128K | $0.01 |
| Claude Sonnet 4.5 | $3.00 | $15.00 | 200K | $0.09 |
| Claude Haiku 4.5 | $0.80 | $4.00 | 200K | $0.02 |
ACOS Model Routing
How the Agentic Creator Operating System routes tasks across model tiers
Opus Tier
claude-opus-4-6
Architecture reviews, research synthesis, complex debugging, multi-file code generation, long-context analysis
$5.00 / $25.00 per 1M tokens
Sonnet Tier
claude-sonnet-4-5
Standard coding, content generation, API integrations, moderate-complexity tasks, production workflows
$3.00 / $15.00 per 1M tokens
Haiku Tier
claude-haiku-4-5
Classification, routing, simple extraction, high-volume processing, real-time chat, metadata tagging
$0.80 / $4.00 per 1M tokens
Benchmark & Ranking Sources
Independent sources for verifying model performance
OpenRouter Model Rankings
Live pricing and performance rankings across all providers
LMArena Leaderboard
Crowdsourced Elo ratings from human preference evaluations
ARC-AGI Benchmarks
Abstract reasoning challenge — the hardest AI benchmark
SWE-bench Verified
Real-world software engineering task evaluation
Artificial Analysis
Independent speed, quality, and pricing benchmarks
SEAL Leaderboards
Scale AI expert evaluations across enterprise tasks
OCI GenAI Model Catalog
Available via Oracle Cloud GenAI Service for enterprise deployment
| Model | Provider | Context | Primary Use Case | EU |
|---|---|---|---|---|
| Cohere Command A Reasoning | Cohere | 256K | Complex reasoning | |
| Cohere Command A Vision | Cohere | 256K | Multimodal | |
| Cohere Embed 4 | Cohere | - | Multimodal embeddings | |
| Cohere Rerank 3.5 | Cohere | - | Search relevance | |
| Llama 4 Maverick | Meta | 256K | Agentic, MoE | - |
| Llama 4 Scout | Meta | 10M | Efficient agentic | - |
| Grok 4.1 Fast | xAI | 2M | Long context, agentic | - |
| Grok Code Fast 1 | xAI | - | Coding specialist | - |
| Gemini 2.5 Pro | 1M | Complex multimodal | - | |
| Gemini 2.5 Flash-Lite | - | Budget, high-volume | - |
Verify current model availability at docs.oracle.com/iaas/Content/generative-ai/pretrained-models.htm
Mixture of Experts (MoE) Architecture
MoE is revolutionizing AI efficiency. Llama 4 Maverick has 400B total parameters but only activates 17B per token — running on a single H100 GPU with quantization while matching much larger dense models.
400B
Total Parameters
17B
Active Per Token
10M
Context (Scout)