This page is built for “best agentic models”, “best llm for agents”, and related searches. Rankings combine tool use, terminal-task, and instruction-following signals so you can pick models for real agent workflows instead of pure chat.
Agents need consistent function calling and strong recovery when tool outputs are imperfect.
Good agentic models can maintain a plan over several steps without collapsing into repetition.
In autonomous systems, slow thinking compounds. Speed and consistency matter as much as raw benchmark quality.
The models below are ranked for autonomous execution, tool use, and multi-step reliability.
| Rank | Model | Quality | Terminal-Bench | τ²-Bench | IFBench |
|---|---|---|---|---|---|
| 1 | GPT-5.2 (xhigh) OpenAI | 50.5 | 44% | 85% | 75% |
| 2 | GLM-5 (Reasoning) Z AI | 49.64 | N/A | N/A | N/A |
| 3 | Claude Opus 4.5 (high) Anthropic | 49.1 | 44% | 90% | 58% |
| 4 | Gemini 3 Pro Preview (high) | 47.9 | 39% | 87% | 70% |
| 5 | GPT-5.1 (high) OpenAI | 47 | 43% | 82% | 73% |
| 6 | Kimi K2.5 (Reasoning) Kimi | 46.73 | N/A | N/A | N/A |
| 7 | Gemini 3 Flash | 45.9 | 36% | 80% | 78% |
| 8 | Gemini 3 Flash Preview (Reasoning) | 45.9 | N/A | N/A | N/A |
| 9 | Claude 4.5 Sonnet Anthropic | 42.4 | 33% | 78% | 57% |
| 10 | MiniMax-M2.5 MiniMax | 41.97 | N/A | N/A | N/A |
If your agents browse, call APIs, run tools, or plan several steps ahead, start here rather than on a generic leaderboard. The best agentic model is the one that stays reliable under execution, not just the one with the strongest chat benchmark.
Once you have a shortlist, open the finalists on Compare and validate whether the provider you want can deliver the right price and latency profile.
Agentic performance overlaps with coding and long-context performance, but it is not the same thing. Use the related pages below if your use case is specialized around software work or large-document reasoning.
SEO Hubs
Start with the evergreen pages below. They align to the highest-intent SEO clusters and are built to stay current as model rankings change.
Live ranking of the best overall AI models by quality, price, speed, and context window.
Current coding leaderboard using LiveCodeBench, Terminal-Bench, and SciCode.
Top open-weight models for self-hosting, Ollama, and low-cost API use.
Best local AI models by hardware tier for self-hosting on Macs, RTX GPUs, and workstations.
Ollama-first picks for coding, chat, reasoning, and low-friction local inference.
Best long-context models for large documents, codebases, and retrieval-heavy workflows.
The live top-ranked model on this page is the best place to start, but the right answer depends on whether you prioritize raw capability, reliability under tool use, or latency in production.
Agentic models can keep track of plans, follow multi-step instructions, call tools reliably, and recover gracefully when a workflow changes.
Not always. Coding strength helps, but agentic performance also depends on planning, tool orchestration, and execution reliability.
Compare the finalists side by side, then run them on the actual tasks your agent will perform. Benchmarks get you the shortlist; production testing makes the final call.