Llama 3 70B Gradient 1048K vs RWKV-7 Goose 2.9B
Llama 3 70B Gradient 1048K (2024) and RWKV-7 Goose 2.9B (2025) are general-purpose language models from Gradient and RWKV Project. Llama 3 70B Gradient 1048K ships a 1.05m-token context window, while RWKV-7 Goose 2.9B ships a Infinite-token context window. This comparison covers specs, pricing, capabilities, benchmarks, provider availability, and production fit. It focuses on practical selection signals rather than broad model-family marketing.
RWKV-7 Goose 2.9B is safer overall; choose Llama 3 70B Gradient 1048K when provider fit matters.
Decision scorecard
Local evidence first| Signal | Llama 3 70B Gradient 1048K | RWKV-7 Goose 2.9B |
|---|---|---|
| Best for | long-context analysis | general production evaluation |
| Decision fit | Long context | Long context |
| Context window | 1.05m | Infinite |
| Cheapest output | - | - |
| Provider routes | 0 tracked | 0 tracked |
| Shared benchmarks | 0 rows | 0 rows |
Decision tradeoffs
- Local decision data tags Llama 3 70B Gradient 1048K for Long context.
- RWKV-7 Goose 2.9B has the larger context window for long prompts, retrieval packs, or transcript analysis.
- Local decision data tags RWKV-7 Goose 2.9B for Long context.
Monthly cost at traffic
Estimate token spend from the cheapest tracked input and output route or tier on this page.
Llama 3 70B Gradient 1048K
Unavailable
No complete token price in local provider data
RWKV-7 Goose 2.9B
Unavailable
No complete token price in local provider data
Cost delta unavailable until both models have sourced input and output token prices.
Switch friction
- No overlapping tracked provider route is sourced for Llama 3 70B Gradient 1048K and RWKV-7 Goose 2.9B; plan for SDK, billing, or endpoint changes.
- No overlapping tracked provider route is sourced for RWKV-7 Goose 2.9B and Llama 3 70B Gradient 1048K; plan for SDK, billing, or endpoint changes.
Specs
| Specification | ||
|---|---|---|
| Released | 2024-04-18 | 2025-03-18 |
| Context window | 1.05m | Infinite |
| Parameters | 70B | 2.9B |
| Architecture | decoder only | decoder only |
| License | Unknown | Apache 2.0 |
| Knowledge cutoff | 2023-12 | - |
Pricing and availability
| Pricing attribute | Llama 3 70B Gradient 1048K | RWKV-7 Goose 2.9B |
|---|---|---|
| Input price | - | - |
| Output price | - | - |
| Providers | - | - |
Pricing not yet sourced for either model.
Capabilities
| Capability | Llama 3 70B Gradient 1048K | RWKV-7 Goose 2.9B |
|---|---|---|
| Vision | No | No |
| Multimodal | No | No |
| Reasoning | No | No |
| Function calling | No | No |
| Tool use | No | No |
| Structured outputs | No | No |
| Code execution | No | No |
| IDE integration | No | No |
| Computer use | No | No |
| Parallel agents | No | No |
Benchmarks
No shared benchmark rows are currently sourced for this pair.
Deep dive
The capability footprint is close: both models cover the core production surface. That makes context budget, benchmark fit, and provider maturity more important than a simple checklist. If your application depends on one integration detail, verify it against the provider route you plan to use, not just the base model listing.
Pricing coverage is uneven: Llama 3 70B Gradient 1048K has no token price sourced yet and RWKV-7 Goose 2.9B has no token price sourced yet. Provider availability is 0 tracked routes versus 0. Treat unknown pricing as an integration gap, then verify the route you will actually call before estimating production spend.
Choose Llama 3 70B Gradient 1048K when provider fit are central to the workload. Choose RWKV-7 Goose 2.9B when provider fit are more important. For production, rerun your own prompts through the exact provider, region, and tool stack you plan to ship. This keeps the decision grounded in measurable tradeoffs instead of brand-level assumptions. It also helps separate model capability from provider packaging, which can change cost and latency. For teams standardizing a stack, that distinction is often the difference between a benchmark win and a reliable deployment.
FAQ
Is Llama 3 70B Gradient 1048K or RWKV-7 Goose 2.9B open source?
Llama 3 70B Gradient 1048K is listed under Unknown. RWKV-7 Goose 2.9B is listed under Apache 2.0. License labels affect whether you can self-host, redistribute weights, or rely only on hosted APIs, so confirm the upstream license before deployment.
When should I pick Llama 3 70B Gradient 1048K over RWKV-7 Goose 2.9B?
RWKV-7 Goose 2.9B is safer overall; choose Llama 3 70B Gradient 1048K when provider fit matters. If your workload also depends on provider fit, start with Llama 3 70B Gradient 1048K; if it depends on provider fit, run the same evaluation with RWKV-7 Goose 2.9B.
What is the main difference between Llama 3 70B Gradient 1048K and RWKV-7 Goose 2.9B?
Llama 3 70B Gradient 1048K and RWKV-7 Goose 2.9B differ most on context, provider coverage, capabilities, or pricing depending on the data currently sourced. Use the specs table first, then validate the model behavior with your own prompts.
Continue comparing
Last reviewed: 2026-05-25. Data sourced from public model cards and provider documentation.