Grok-1
grok-1
Last refreshed 2026-04-18. Next refresh: weekly.
Grok-1 has model metadata, but missing tracked provider pricing keeps it from being a default production pick.
Decision context: Coding task fit, 0 tracked provider routes, and research from 2026-01-01.
Use it for
- Teams evaluating general LLM work
Do not use it for
- Cost-sensitive launches that need sourced token pricing
- Vision or document-understanding workloads
- Strict JSON or tool-calling flows
Cheapest output
-
No tracked output price
Provider routes
0
No provider route in seed
Quality / dollar
Unknown
No task benchmark coverage yet
Freshness
2026-01-01
Researched 137d ago
Top use-case fit
No primary decision-task fit is mapped for this model yet.
Provider price ladder
No tracked provider token pricing is available for this model yet.
Benchmark peer barsfor Coding
No task-mapped benchmark peers are available for this model yet.
Migration checks
No linked migration route is available for this model yet.
About
Grok-1, created by xAI, is a formidable 314-billion parameter Mixture-of-Experts (MoE) language model. It boasts a sophisticated architecture with 8 experts, leveraging 2 for each token input, spread across 64 layers and equipped with 48 attention heads per query. This vast model was trained from scratch using a specially crafted training stack based on JAX and Rust, finishing its pre-training phase by October 2023. Released as a base model under the permissive Apache 2.0 license, its open-source framework allows both commercial and non-commercial applications, though it lacks fine-tuning for specific tasks. Benchmarks highlight Grok-1's superior reasoning on various tasks but recognize its potential for generating inaccuracies ("hallucinations"). Running on a local setup requires substantial hardware, including a multi-GPU system, for efficient performance.
