RWKV-7 Goose 2.9B
rwkv-7-goose-2.9b
Last refreshed 2026-05-25. Next refresh: weekly.
RWKV-7 Goose 2.9B has model metadata, but missing tracked provider pricing keeps it from being a default production pick.
Decision context: Long context task fit, 0 tracked provider routes, and research from 2026-05-25.
Use it for
- Teams evaluating long context
- Workloads that can use a Infinite context window
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
2026-05-25
Researched today
Top use-case fit
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.
Benchmark peer barsfor Long context
No task-mapped benchmark peers are available for this model yet.
Migration checks
No linked migration route is available for this model yet.
About
RWKV-7 Goose 2.9B is the largest released model in the RWKV-7 Goose World3 series. Built on the seventh-generation RWKV architecture with the Generalized Delta Rule and dynamic state evolution, it achieves competitive benchmark performance against transformer models of equivalent scale. Trained on 3.1 trillion tokens from the World v3 multilingual corpus (100+ languages, BF16). As a pure recurrent architecture, it requires constant O(1) memory during inference (no KV cache) and processes sequences in linear O(n) time. Licensed Apache 2.0.
RWKV-7 Goose 2.9B has a Infinite context window.
Capabilities
No model capability flags are currently sourced.
Specifications
Created by
Linear complexity language models combining the efficiency of RNNs with the parallelism of Transformers