Agents-A1
Agents-A1 is a released rag, agents, and long context model with open-source and 262k context; evaluate it while provider pricing coverage matures.
Use it for
- Teams evaluating rag, agents, and long context
- Workloads that can use a 262k context window
Do not use it for
- Cost-sensitive launches that need sourced token pricing
- Teams that need a tracked hosted API route today
- Family
- Agents-A1
- Released
- 2026-06-26
- Context
- 262k
- Parameters
- 35B total, 3B active
- Architecture
- Mixture of Experts
- Specialization
- general
- Openness
- Open source
- License
- Apache 2.0OSI-approvedCommercial use: permitted
- Weights
- Available
- Code
- Unknown
- Training
- Multi-stage
No tracked provider token pricing is available yet.
About
Agents-A1 is Intern Science's 35B-A3B open-source Mixture-of-Experts agentic model for long-horizon search, engineering, scientific research, instruction following, and tool calling. It is trained with a three-stage recipe that combines full-domain supervised fine-tuning, domain-level teacher models, and multi-teacher on-policy distillation over knowledge-action trajectories. The model supports vision-language inputs, reasoning traces, and tool/function calling through standard LLM runtimes such as SGLang and vLLM, with a recommended served context length of 262,144 tokens. Intern Science reports strong vendor scores on BrowseComp, HLE with tools, IFEval, and scientific/engineering agent benchmarks; teams should treat these as model-card scores until independently reproduced.
Agents-A1 is Intern Science's 35B-A3B open-source Mixture-of-Experts agentic model for long-horizon search, engineering, scientific research, instruction following, and tool calling. It is trained with a three-stage recipe that combines full-domain supervised fine-tuning, domain-level teacher models, and multi-teacher on-policy distillation over knowledge-action trajectories. The model supports vision-language inputs, reasoning traces, and tool/function calling through standard LLM runtimes such as SGLang and vLLM, with a recommended served context length of 262,144 tokens. Intern Science reports strong vendor scores on BrowseComp, HLE with tools, IFEval, and scientific/engineering agent benchmarks; teams should treat these as model-card scores until independently reproduced.
Agents-A1 has a 262k-token context window.
Top use-case fit: coding, agents, and build tasks
RAG
Included by capability and metadata signals in the decision map.
Agents
Included by capability and metadata signals in the decision map.
Long context
Included by capability and metadata signals in the decision map.
Provider price ladder
No tracked provider token pricing is available for this model yet.
Capabilities
Benchmark peer barsfor RAG
No task-mapped benchmark peers are available for this model yet.
Benchmark scores(3)
| Benchmark | Score | Version | Source |
|---|---|---|---|
| BrowseComp | 75.5 | BrowseComp accuracy, vendor-reported on Agents-A1 model card | https://huggingface.co/InternScience/Agents-A1 |
| Humanity's Last Exam — With Tools | 47.6 | Humanity's Last Exam with tools accuracy, vendor-reported on Agents-A1 model card | https://huggingface.co/InternScience/Agents-A1 |
| Instruction-Following Evaluation | 94.8 | IFEval accuracy, vendor-reported on Agents-A1 model card | https://huggingface.co/InternScience/Agents-A1 |
Migration checks
No linked migration route is available for this model yet.
API versions
InternScience/Agents-A1InternScience/Agents-A1-FP8InternScience/Agents-A1-Q4_K_M-GGUFInternScience/Agents-A1-Q8_0-GGUFInternScience/Agents-A1-F16-GGUFFrequently asked questions
What is the context window of Agents-A1?
Agents-A1 has a context window of 262k tokens.
When was Agents-A1 released?
Agents-A1 was released on 2026-06-26.
What benchmarks has Agents-A1 been tested on?
Agents-A1 has been evaluated on 3 benchmarks, including BrowseComp, Humanity's Last Exam — With Tools, Instruction-Following Evaluation.
No tracked provider token pricing is available yet.