Best LLM for agents (October 2026)
As of 12 Oct 2026, the best LLM for agents and tool use on independent benchmarks is Muse Spark 1.3 (max) by Meta (agents score 70.3), ahead of o3 (agents score 70.2) and Claude Fable 5.1 (max) (agents score 70.1).
Ranked on the agents-and-tools category: function calling, multi-step tool use and agentic task boards such as Terminal-Bench, BFCL and τ²-bench. Models need results on at least two of them.
133 models qualify · data as of 12 Oct 2026 · rebuilt once a day (the run starts at 22:03 UTC)
Muse Spark 1.3 max#1 here: agents score 70.3Best value
DeepSeek V3.2 thinkingmost index points per dollar among the top 15 (55.4 at $0.315/M)Best open weights
Qwen3.8 27B xhighhighest-ranked model here you can run yourself (#9)| # | Model | Agents score | Index | Price $/M | Speed tok/s |
|---|---|---|---|---|---|
| 1 | Muse Spark 1.3maxMeta | 70.3 | 67.7 | $2.00 | 175 |
| 2 |  o3OpenAI | 70.2 | 59.7 | $3.50 | 116 |
| 3 |  Claude Fable 5.1maxAnthropic | 70.1 | 70.8 | $20.00 | 70 |
| 4 | Claude Sonnet 5.5maxAnthropic | 69.5 | 67.6 | $4.00 | 141 |
| 5 | Claude Opus 5.5maxAnthropic | 69.0 | 72.0 | $8.00 | 96 |
| 6 | Claude Opus 4.6Anthropic | 68.9 | 63.1 | $10.00 | 40 |
| 7 | GPT-6 AstramaxOpenAI | 68.8 | 70.2 | $20.00 | 47 |
| 8 | Claude Opus 4.7Anthropic | 67.5 | 63.7 | $10.00 | 81 |
| 9 | Qwen3.8 27BxhighAlibaba | 67.2 | 58.5 | $1.13 | 46 |
| 10 | GPT-5.6 SolmaxOpenAI | 66.5 | 67.5 | $8.00 | 74 |
| 11 |  Kimi K3maxMoonshot AI | 66.2 | 65.5 | $6.00 | 41 |
| 12 | Muse SparkMeta | 66.0 | 64.6 | – | – |
| 13 | DeepSeek V3.2thinkingDeepSeek | 66.0 | 55.4 | $0.315 | 12 |
| 14 | Claude Opus 5highAnthropic | 65.1 | 68.3 | $10.00 | 54 |
| 15 | Claude Fable 5maxAnthropic | 65.0 | 69.1 | $20.00 | 65 |
Full ranked list (133 models) · Muse Spark 1.3 vs o3 · Best for coding agents, with the weighting stated · Methodology
Best LLM for agents: questions
- What is the best LLM for agents and tool use in October 2026?
- As of 12 Oct 2026, the best LLM for agents and tool use on independent benchmarks is Muse Spark 1.3 (max) by Meta (agents score 70.3), ahead of o3 (agents score 70.2) and Claude Fable 5.1 (max) (agents score 70.1). BenchLeader reconciles 210 benchmarks from 42 benchmark publishers and rebuilds the ranking once a day (the run starts at 22:03 UTC).
- Which is the best value?
- DeepSeek V3.2 (thinking) gives the most BenchLeader Index points per dollar among the top 15 here: 55.4 at $0.315 per million tokens blended, against $2.00 for Muse Spark 1.3.
- What is the best open-weights option?
- Qwen3.8 27B (xhigh) by Alibaba is the highest-ranked open-weights model on this list, at #9.
- How is this ranked?
- Ranked on the agents-and-tools category: function calling, multi-step tool use and agentic task boards such as Terminal-Bench, BFCL and τ²-bench. Models need results on at least two of them. Every score comes from an independent publisher and links to its source on the model page; self-reported launch numbers are excluded.
Cite as: BenchLeader, “Best LLM for agents (October 2026)”, https://www.benchleader.com/best/llm-for-agents, data as of 12 Oct 2026.