Find the best AI for what you actually need

Google's reasoning-optimized flagship, released February 19, 2026, and currently the #1 ranked model on the Artificial Analysis Intelligence Index (score: 57 out of 115+ models). Gemini 3.1 Pro is a direct upgrade to Gemini 3 Pro — same 1M token context window and same $2/$12 pricing — but with dramatically improved reasoning. AA independently measures it at 94.1% GPQA Diamond, 44.7% HLE, and 95.6% τ²-bench — top of field on all three. The API exposes three thinking tiers (Low / Medium / High) and a 65,536-token output window — the largest published output context of any frontier model. A dedicated custom-tools API endpoint is available for agentic pipeline use. Currently in preview — generally available soon.

Google's November 2025 flagship — deprecated March 9, 2026, replaced by Gemini 3.1 Pro at the same $2/$12 per 1M token price. It led 13 of 16 major benchmarks at launch: 90.8% GPQA Diamond, 87.1% τ²-bench, 138 t/s output speed, and a real 1M-token context window. Two things to know before deploying: an 88% hallucination rate (AA-Omniscience) that requires Search grounding to mitigate, and verbosity that inflates real API costs 4–5× above the listed rate. If you're starting fresh, use 3.1 Pro. Already on 3 Pro? The migration is a model string change.

Google's December 2025 Flash model — distilled from Gemini 3 Pro, and in a result that embarrassed the larger model, it beats Pro on SWE-bench Verified (78% vs 76.2%). At $0.50/$3.00 per 1M tokens with a 1M context window and 214 t/s output speed, it's now the default model powering the Gemini app and AI Mode in Google Search for hundreds of millions of users. The intelligence-to-cost ratio is unusual: GPQA Diamond 90.4%, near-Pro level science reasoning, at one-quarter the API price. One thing to know before production use: a 91% hallucination rate that needs Search grounding to control, and text-only output — no image or audio generation.

Released March 5, 2026, GPT-5.4 is OpenAI's most capable frontier model for professional work. It merges the coding depth of GPT-5.3-Codex with leading knowledge-work, computer-use, and agentic tool capabilities into a single model. On GDPval it beats or ties human experts on 83% of tasks (up from 70.9% on GPT-5.2). It's the first general-purpose OpenAI model with native computer-use, hitting 75% on OSWorld-Verified and surpassing human performance. The 1M token context window (experimental in Codex), tool search for efficient MCP integration, and 33% fewer hallucinated claims make it the new default for enterprise automation.

Released December 11, 2025 under the internal codename 'Garlic', GPT-5.2 is OpenAI's flagship reasoning model. It beats or ties human industry experts on 70.9% of GDPval knowledge work tasks, scores 100% on AIME 2025 without tools, and runs at a hallucination rate under 1% with browsing active. The 400K context window, 5-tier thinking budget, and 90% cached-input discount make it the default choice for enterprise automation and agentic pipelines.

Released February 5, 2026, GPT-5.3-Codex is OpenAI's most capable agentic coding model — combining the coding depth of GPT-5.2-Codex with the reasoning and professional knowledge of GPT-5.2, at 25% faster speed. It powers the Codex product (chatgpt.com/codex) and runs autonomously for hours: writing features, fixing bugs, proposing PRs, and operating computers end-to-end. It's the first OpenAI model self-classified as 'High capability' in cybersecurity, delaying API access. Token efficiency is the clearest competitive edge — it uses roughly 3× fewer tokens than Claude Code on equivalent tasks.

Anthropic's mid-tier model and the practical daily-driver recommendation. Sonnet 4.6 sits just below Opus in raw intelligence but costs 80% less. It's the best model for writing, analysis, and long-document work for anyone who isn't running enterprise-scale inference.

Anthropic's most powerful model, released February 4, 2026. Opus 4.6 leads the industry on enterprise expert tasks (GDPval-AA Elo 1606 — 144 points above GPT-5.2), agentic computer use (OSWorld 72.7%), and long-context retrieval (MRCR v2: 76% accuracy at 1M tokens). Its 1M-token context window is in beta; standard is 200K. The price — $5/$25 per 1M tokens — reflects the positioning: reach for it when output quality has direct business consequences.

OpenAI's small-but-smart model and the best value in the GPT-5 family. At $0.25/$2.00 per 1M tokens it costs 7× less than GPT-5.2 while delivering an AA Intelligence Index of 41 — higher than Claude Haiku and Gemini Flash. The 400K context window and multimodal input make it a strong default for cost-sensitive production pipelines.