Agents-A1 released
InternScience · Model release
Source confirmed
Data as of October 5, 2026 · How the score is built
CurrentOpen WeightReasoning
Released Jun 26, 2026262K context
Agents-A1
Decision readingAgents-A1 scores 53.2 out of 100 and ranks #72 of 212. This profile shows 6 source-displayable benchmark rows; its strongest eligible category is Agentic at #46. No comparable first-party API price is published in the catalog.
Released Jun 26, 2026 — see all recent releases
Agents-A1 will be repriced, updated or retired. Get each notice with its source and date. Follow model changes
Decision snapshot
Each value carries a field reference instead of floating alone. Markers compare this model with the current ranked and priced catalog; they are not absolute quality thresholds.
Capability
53.2/100
field median 51#72 of 212 ranked models
Public
#72of 212
Verified —
Price
Not listed
input median $0.95No comparable first-party hosted token rate
Speed
Not measured
field median 90 tok/sTime to first token not measured
Context
262Ktokens
field median 256,000Reported for this model; direct source link not stored
Strongest published evidence
Agentic ranks #46. Particularly useful for coding agents, browser research, and computer-use workflows.
Validate before choosing
6 published rows leave some tracked benchmark slots empty. No comparable first-party API token rate is published.
Source-linked · 6 displayable benchmark rows
Follow model changesCategory score record
Scores and ranks appear only where published evidence can be displayed. The table keeps the score, weight, cohort, and evidence state together.
| Category | Score | Rank | Percentile | Weight | Benchmarks | Evidence |
|---|---|---|---|---|---|---|
| AgenticRank #46 of 119Percentile 62ndWeight 22%3 benchmarksVerified | 44.9 | 3 benchmarks | Verified | |||
| CodingWeight 20%0 benchmarksNot measured | Not measured | 0 benchmarks | Not measured | |||
| ReasoningRank Not rankedWeight 17%1 benchmarkVerified | 35.2 | 1 benchmark | Verified | |||
| MultimodalWeight 12%0 benchmarksNot measured | Not measured | 0 benchmarks | Not measured | |||
| KnowledgeRank Not rankedWeight 12%1 benchmarkVerified | 67.8 | 1 benchmark | Verified | |||
| MultilingualWeight 7%0 benchmarksNot measured | Not measured | 0 benchmarks | Not measured | |||
| Inst. FollowingWeight 5%1 benchmarkVerified | Score pending | 1 benchmark | Verified | |||
| MathWeight 5%0 benchmarksNot measured | Not measured | 0 benchmarks | Not measured |
6 of 649 tracked benchmark slots have displayable evidence · bars run 0–100
Coverage detailsHow much of this is verified
Coverage is split by category so a strong number never hides a thin evidence base. Verified means the row is tied to a published source; provisional rows remain visible but separate.
- Agentic3/3 verified
- CodingNot measured
- Reasoning1/1 verified
- MultimodalNot measured
- Knowledge1/1 verified
- MultilingualNot measured
- Inst. Following1/1 verified
- MathNot measured
Verified sourceProvisionalNot measured
Capability shape
Each axis shows percentile within that category’s eligible cohort. The comparison outline is the median of the six nearest public-score peers; a collapsed vertex means the category is not rank-eligible.
Agents-A1 category percentile values
- Agentic62nd percentile
- CodingNot eligible
- ReasoningNot eligible
- MultimodalNot eligible
- KnowledgeNot eligible
- MultilingualNot eligible
- Instruction followingNot eligible
- MathNot eligible
The dashed outline is median of 6 nearest peers.
Eligible category ranks
- Agentic#46/119
- CodingNot ranked
- ReasoningNot ranked
- MultimodalNot ranked
- KnowledgeNot ranked
- MultilingualNot ranked
- Inst. FollowingNot ranked
- MathNot ranked
Top decileTop quartileMid-fieldNot eligible
Benchmark ledger
Agentic opens by default. The marker compares each value with the best source-verified result in the catalog; provisional leaders do not set the reference. Expand the remaining categories for every published row.
Agentic3 rows
| Benchmark | Score | Versus best verified row | Gap | Weight | Evidence |
|---|---|---|---|---|---|
| BrowseComp | Score75.5% | Versus best verified row Best verified: Atria Dawn Preview · 92.5% | Gap17 behind | Weight8% ref. weight | Provider exact |
| HLE w/ toolsHumanity's Last Exam with tools | Score47.6% | Versus best verified row Best verified: Claude Opus 5.5 · 67.7% | Gap20.1 behind | Weight3% ref. weight | Provider exact |
| VITA-Bench | Score38.8% | Versus best verified row Best verified: Qwen3.7 Max · 47.9% | Gap9.1 behind | WeightDisplay only | Provider exact |
Reasoning1 row
| Benchmark | Score | Versus best verified row | Gap | Weight | Evidence |
|---|---|---|---|---|---|
| LongBench v2 | Score60.2% | Versus best verified row Best verified: Qwen3.8 Max · 66.3% | Gap6.1 behind | WeightWeighted 25% | Provider exact |
Knowledge1 row
| Benchmark | Score | Versus best verified row | Gap | Weight | Evidence |
|---|---|---|---|---|---|
| HLEHumanity's Last Exam | Score47.6% | Versus best verified row Best verified: Claude Fable 5.1 · 65% | Gap17.4 behind | Weight44% ref. weight | Provider exact |
Inst. Following1 row
| Benchmark | Score | Versus best verified row | Gap | Weight | Evidence |
|---|---|---|---|---|---|
| IFEvalInstruction-Following Eval | Score94.8% | Versus best verified row Best verified: Qwen3.5-27B · 95% | Gap0.2 behind | WeightDisplay only | Provider exact |
Bars run 0–100; the dark tick marks the best source-verified value
All 6 rowsLineage
The sequence follows explicit supersedes links. Each score is estimated for that model; a relative can inform a sparse estimate but never sets a floor, so a newer release can score below an earlier one. Scores and prices remain blank when the corresponding public row or first-party rate is unavailable.
Radar
Full release historyAgents-A1 release history
Radar confirmed these at the source. Use Agents-A1 in your work? Explore Radar to follow supported changes and choose your alerts.
Radar
Spec sheet
Each documented value carries its source. Missing fields stay visible as not sourced or not published, rather than disappearing from the page.
- API model ID
- Not published
- Context window
- 262K
- Maximum output
- Not sourced yet
- Knowledge cutoff
- Not sourced yet
- Input modalities
- Not sourced yet
- Output modalities
- Not sourced yet
- Parameters
- Not sourced yet
- Availability
- Not sourced yet
- Cloud regions
- Not tracked yet
- Lifecycle
- Current
- API capabilities
- Tool calling, structured outputs, and batch support are not tracked yet
- Prompt caching
- Not documented in the pricing record
- Self-host
- Open weights available; hardware estimate not sourced
- Rate limits
- Not tracked yet
How to read this profile
The visual layer above carries the decisions. These notes preserve the model, ranking, coverage, and family context behind the numbers.
Agents-A1 ranks #72 of 212 on the public leaderboard with a score of 53.24/100. It does not yet have enough sourced coverage for a verified position.
Agents-A1 is a open weight model with a 262K context window. It uses an explicit reasoning mode, which can improve complex problem solving while adding latency and token use.
Official exact-value snapshot from the InternScience Agents-A1 Hugging Face model card and technical report. BenchLM maps only directly comparable public rows: BrowseComp, SciCode, HLE with tools, LongBench-v2, IFEval, tau2-Bench, and VitaBench. FrontierScience-Olympiad, FrontierScience-Research, Seal0, HiPhO, XBench-DS-2510, GAIA, IFBench, MatTools, and MolBench-bind remain outside the current weighted schema.
Agents-A1 sits in the Agents-A1 family with Agents-A1-4B, Agents-A1-F16-GGUF, Agents-A1-FP8, Agents-A1-Q4_K_M-GGUF, Agents-A1-Q8_0-GGUF. 6 of 649 tracked benchmark slots currently have displayable evidence. Missing categories stay blank.
Its strongest eligible category is Agentic at #46. particularly useful for coding agents, browser research, and computer-use workflows.
Last updated October 5, 2026. Runtime fields remain blank until a sourced snapshot exists.
Deployment options
Self-host and provider-specific paths stay separate from benchmark evidence so operating constraints are visible before a score becomes the whole decision.
Published weights are available, but BenchLM does not yet have a sourced parameter and VRAM profile for this exact model. Hardware cost estimates stay unavailable until that sizing record is complete.
Estimate VRAM from known parametersQuestions
How does Agents-A1 perform overall in AI benchmarks?
Agents-A1 ranks #72 out of 212 models on the public BenchAlign leaderboard, with a score of 53.24/100. Its evidence status is Estimated, and this profile shows 6 source-displayable benchmark rows. The label describes evidence depth, not a provider quality claim; inspect category rows before choosing a workload.
Is Agents-A1 good for knowledge and understanding?
Agents-A1 has source-displayable benchmark coverage for knowledge and understanding, but the public category table does not assign it a rank there. The individual rows remain available for inspection. A missing category position means the evidence threshold was not met; it does not convert the model's unmeasured work into a zero.
Is Agents-A1 good for reasoning and logic?
Agents-A1 has source-displayable benchmark coverage for reasoning and logic, but the public category table does not assign it a rank there. The individual rows remain available for inspection. A missing category position means the evidence threshold was not met; it does not convert the model's unmeasured work into a zero.
Is Agents-A1 good for agentic tool use and computer tasks?
Agents-A1 ranks #46 out of 119 eligible models for agentic tool use and computer tasks, with a public category score of 44.9/100. Higher-ranked alternatives are available for workloads where this category decides the choice. Check the underlying rows before treating the aggregate as a workload guarantee.
Is Agents-A1 good for instruction following?
Agents-A1 has source-displayable benchmark coverage for instruction following, but the public category table does not assign it a rank there. The individual rows remain available for inspection. A missing category position means the evidence threshold was not met; it does not convert the model's unmeasured work into a zero.
Is Agents-A1 open source?
Agents-A1 is an open-weight model from InternScience. Its weights can be downloaded for local or hosted deployment, subject to the published license. Open weight does not automatically mean open source: training data and training code may remain private, and commercial restrictions can still apply.
Which sibling models are related to Agents-A1?
Agents-A1 belongs to the Agents-A1 family. Related tracked variants include Agents-A1-4B, Agents-A1-F16-GGUF, Agents-A1-FP8, plus 2 more. A sibling link indicates shared lineage or a documented configuration relationship; it does not mean the variants have identical pricing, context limits, benchmark evidence, or deployment behavior. Compare before switching.
Does Agents-A1 have full benchmark coverage on BenchLM?
No. Agents-A1 currently has 6 source-displayable rows across 649 tracked benchmark slots. The profile exposes published, non-generated evidence and leaves missing categories blank until an exact evaluation is available. Coverage describes how much was measured; it is not a penalty added to an individual benchmark result.
What is the context window size of Agents-A1?
Agents-A1 has a reported context window of 262K in the exact-model catalog record. The value stays visible, but the profile marks its source link as unavailable instead of presenting it as directly documented. Maximum output length remains separate because providers often publish a different limit.