Inkling 2 Small, in numbers.
Everything Thinking Machines Lab has published about their second-generation model — specifications, prices, benchmark scores and release status — collected in one place and re-checked every twelve hours.
Inkling 2 Small is a 594-billion-parameter Mixture-of-Experts model from Thinking Machines Lab, released on Nov 5, 2026, with 17B parameters active per token, native image understanding, and a context window advertised at up to one million tokens. It is currently available through Tinker under the Tinker Terms of Use; the company says Apache 2.0 weights are coming around Nov 12, 2026.
- Total parameters
- 594B
- Active per token
- 17B
- Context, advertised
- 1Mtokens
- Context, served
- 64K / 256Ktokens
- Output price
- $1/ 1M tok
- Intelligence Index
- 31rank 6 / 36
What changed, and what is pending
Full changelog Weights are not out yet. The announcement committed to Apache 2.0 weights in the week after launch, and that window closed on Nov 12, 2026. No weights repository has appeared, so the model remains API-only in practice. Follow the tracker for what would have to change.
- Initial snapshot
Selected benchmarks
All 71 rows across 13 models| Benchmark | Inkling 2 Small | GLM-5.3-Flash | DeepSeek-V4.1-Flash-1017 | Muse Spark Open | Kimi K3 |
|---|---|---|---|---|---|
| FrontierCode v2.0 | 25.4% | 14.2% | 28.5% | 7.6% | 17.3% |
| DeepSWE v1.1 | 72.1% | 63.4% | 77% | 60% | 68.5% |
| Terminal Bench Science v0.1 | 5.7% | 4.8% | 12.9% | 1.9% | 8.1% |
| Terminal Bench v4.0 | 13.1% | 32.8% | 33.8% | 8.1% | 12.6% |
| Terminal Bench 2.1 · Inkling 2 Small: Pi harness | 85.1% | 84.3% | 78.4% | 76.4% | 88.3% |
| Terminal Bench v2.1 (Terminus) | 81.3% | 84.3% | – | 76.4% | 85% |
| Vibe Code Bench v1.1 | 81.6% | 30.8% | 87.7% | 76.2% | 85% |
| Sudo L7 | 14.1% | – | – | – | 13.9% |
| SWE-Marathon v1.1 | 38.8% | 38.8% | 40% | – | 48.1% |
| SWEBench Multilingual | 81.2% | 88.9% | 82.9% | 77.5% | 91.4% |
| SWEBench Multimodal v2 | 43.1% | – | – | – | 44.2% |
| SWEBench Pro v2 (Hard) | 86.3% | – | – | 82.4% | 88.2% |
| SWEBench Pro v2 (Full) | 97.7% | – | – | 95% | 97.7% |
| SWEBench Verified | 82.2% | 92% | 84.6% | 80% | 93.4% |
Price
Pricing detail| Variant | Prefill | Cached prefill | Sample | Train |
|---|---|---|---|---|
| 64K context | $0.3 | $0.03 | $1 | $1.5 |
| 256K context | $0.3 | $0.03 | $1 | $3 |
At a glance
- Architecture
- 48 layers, sparse MoE routing each token to 8 of 384 experts; hybrid local/global attention
- Vision
- Native image input via a 292M-parameter vision encoder, 20×20-pixel patches with 2×2 spatial pooling. Output is text only.
- Numerics
- MXFP8, NVFP4
- License now
- Tinker Terms of Use
- License intended
- Apache 2.0 · targeted Nov 12, 2026
- Speed, third-party
- 88 tok/s output, 63.83s to first token, 28.5 minutes per Intelligence Index task (median for comparable models: 7.5)