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Sage-A1.5 by InternScience scores 62.95 overall and carries a context window of 262K tokens — observed 2026-10-23.
InternScience · Open Weight · rank 44 · bench-align-v5
Self-hostedSeven axes from the ranking source. A missing axis is drawn as a gap.
Measured values with the date they were observed. Nothing is inferred from a sibling model or a provider claim.
Time to first token: latency to the first answer chunk (Artificial Analysis, via BenchLM). Reasoning models include thinking time, so values can run to tens or hundreds of seconds.
Evidence key: ObservedUnavailable
| Measurement | Value | Observed | Last good | Evidence |
|---|---|---|---|---|
| Time to first token | Unavailable | Unavailable | Unavailable | |
| Throughput | Unavailable | Unavailable | Unavailable |
Regional or per-endpoint measurements appear only when the API supplies them; none are modelled here.
Every published price component, including cache reads and writes.
10 conversations per day × 8 messages × 22 active days, 1200 input and 400 output tokens per message, no cache. This uses the same calculator as the cost simulator, so an unavailable applicable rate makes the example unavailable too.
13 matched benchmark rows with their published value, unit, and provenance.
| Benchmark | Value | Tasks | Difficulty | Provenance |
|---|---|---|---|---|
| FrontierScience Research FrontierScience Research | 48.3 | Scientific research problems | Frontier scientific research | Muse Spark Eval Methodology |
| Benchmark | Value | Tasks | Difficulty | Provenance |
|---|---|---|---|---|
| SWE-bench Pro SWE-bench Pro | 61.2 | 1,865 repository problems | Long-horizon professional engineering | SWE-Bench Pro: Can AI Agents Solve Long-Horizon Software Engineering Tasks? |
| SWE Multilingual SWE Multilingual | 72.7 | Multilingual software-engineering tasks |
Lifecycle events the source associates with this model, plus what this profile does not claim.
That is not evidence the model has no lifecycle plan — only that this source published none.
| Professional software engineering |
| MiniMax M2.7: Early Echoes of Self-Evolution |
| SciCode Scientific Code Benchmark | 44.3 | — | — | BenchLM |
| Benchmark | Value | Tasks | Difficulty | Provenance |
|---|---|---|---|---|
| AA-LCR Artificial Analysis Long Context Reasoning | 81.0 | Long-context reasoning tasks | Long-context reasoning | Artificial Analysis model benchmarks |
| CritPt Critical Physics Tasks | 20.0 | Research-level physics questions | Research-level physics reasoning | CritPt Benchmark Leaderboard |
| Benchmark | Value | Tasks | Difficulty | Provenance |
|---|---|---|---|---|
| IFBench Instruction Following Benchmark | 81.6 | — | — | BenchLM |
| Benchmark | Value | Tasks | Difficulty | Provenance |
|---|---|---|---|---|
| BrowseComp BrowseComp | 81.7 | Research questions requiring browsing | Hard web research | BrowseComp |
| HLE w/ tools Humanity's Last Exam with tools | 55.1 | Expert questions with tool use | Frontier tool-augmented reasoning | DeepSeek-V4 Technical Report |
| PinchBench PinchBench | 90.0 | 23 OpenClaw agent tasks | Long-horizon agent workflows | About PinchBench |
| MLE-Bench Lite MLE-Bench Lite | 65.2 | Low-resource ML competitions | Agentic machine learning | MiniMax M2.7: Early Echoes of Self-Evolution |
| VITA-Bench VITA-Bench | 45.4 | Interactive consumer-service agent tasks | Long-horizon real-world workflows | VitaBench: Benchmarking LLM Agents with Versatile Interactive Tasks in Real-world Applications |
| GAIA General AI Assistants | 95.1 | — | — | BenchLM |