webAI Open-Sources TwIL-8B, a Small Model Approaching Frontier Coding and Math
webAI has open-sourced TwIL-8B, an 8.8B-parameter model built on IBM's Granite 4.2 8B and tuned for math, coding and instruction following. It reportedly fits in a 4.98 GiB quantized file that runs on CPUs or modest GPUs, scoring 81.6% on LiveCodeBench and reaching roughly 92-93% of frontier-model performance on coding and instruction following.
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Rohan Paul (@rohanpaul_ai) · 2026-11-05 19
webAI (@thewebAI) just open-sourced TwIL-8B, an 8.8B model built on IBM’s Granite 4.2 8B and trained for math, coding and following instructions.
TwIL-8B fits in a 4.98 GiB quantized file that runs on a CPU or modest graphics card, putting near-frontier coding and math on hardware people already own.
scores 81.6% on LiveCodeBench, 16.0 points above Qwen3.5-9B and ahead of Google’s Gemma 4 31B, a model 3.5x its size.
Against GPT-5.5, Claude Opus 4.8 and Grok 4.3, TwIL-8B reaches 93% of the best frontier score on coding and 92% on instruction following, beating Claude Opus 4.8 on IFBench by 12.2 points.
A final training stage that rewards shorter reasoning lets TwIL-8B solve AIME 2026 problems with 38% fewer tokens than Qwen3.5-9B, while posting the highest MATH-500 score in its comparison at 98.2%.
↳ 引用 @Davidstout (David Stout): Modest intelligence is arriving faster than most people realize.
Today, we're open-sourcing TwIL-8B.
Just 8.8 billion parameters, yet approaching frontier-model scores on several difficult benchmarks:
• 93% of frontier performance on coding
• 92% on instruction following
• 90% on contest mathematics
All from a model small enough to run on your own hardware.
But the benchmarks aren't the most important part of this announcement.
For years, the AI industry has focused on building the most capable model, regardless of the cost required to run it.
I believe that equation is changing.
The next era of AI will be defined by the cost of completing work. Not simply the intelligence of the model, but how efficiently that intelligence can accomplish the task.
If a model with 8 billion parameters can reliably complete the same work as one with hundreds of billions, why pay for the larger model?
As smaller models become more capable, intelligence becomes something we can distribute, specialize, and run across the hardware we already own.
That's the future we're building at @thewebAI
TwIL-8B is available today. Open weights.
And this is just the first of several announcements we're making today.
HF Link:
