Model Detail
Cohere: Command R (08-2024)
—Cohere: Command R (08-2024) is a large language model released by Cohere. And supports text->text inputs.
Cohere: Command R (08-2024) is priced at $0.15/M input tokens and $0.6/M output tokens. Operationally the model offers a 128K-token context window, which matters when sizing it for prompt-heavy or latency-sensitive workloads. At this input rate the model sits in the commodity tier and is suitable for high-volume workloads where per-call cost dominates the decision.
The published knowledge cutoff is 2024-03-31, so newer events will not be reflected in zero-shot answers without retrieval.
Cohere: Command R (08-2024) is best fit for general-purpose chat and instruction-following workloads, and high-volume batch jobs where per-call cost dominates the budget. Treat this as a starting matrix rather than a benchmark verdict — the right deployment usually depends on the specific evaluation suite that mirrors your workload.
DexFLEX: Contact-Aware Foundation Controller for Command-Guided Dexterity
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Constrained Command-Conditioned Reinforcement Learning with Bandit Strategy Selection in Real-Time Strategy Games
arXiv:2610.11663v1 Announce Type: new Abstract: Deep reinforcement learning agents reach strong performance in real-time strategy games but can be brittle against opponents outside their training distribution. Separating strategic command selection from learned unit control allows different strategi
AstroForge is putting AI in command of its next spacecraft
Autonomy-1 will have a small, transformer-based AI model taking charge of a space probe.
From Intent to Action: Benchmarking LLM Safety in Vehicle Voice Command Authorization
arXiv:2609.19630v1 Announce Type: new Abstract: Large language models (LLMs) are increasingly integrated into vehicle voice assistants. But linking natural-language requests to vehicle functions creates a safety-critical authorization problem. Before executing a command, the system must choose wheth
SENTINEL: A Multi-Pathway Architecture for Detecting Living-Off-the-Land APT Attacks on Windows Command Lines
arXiv:2609.14593v1 Announce Type: cross Abstract: Living-Off-the-Land (LOTL) is the dominant evasion technique of Advanced Persistent Threat (APT) actors, exploiting legitimate Windows utilities to conduct malicious operations without deploying custom malware and enabling state-sponsored campaigns t
Yes, you can now order DoorDash from the command line
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