Kimi K3 just became the most important model in agentic coding — because Cognition used it as the base for SWE-2, the new 50%-on-FrontierCode model that undercut the frontier by 64%. But what is Kimi K3 itself actually worth, head-to-head against the models it's challenging? We pulled live pricing and benchmarks to find out.
The Contenders
This is a battle between three very different philosophies:
- Kimi K3 (Moonshot AI) — the 2.8-trillion-parameter open-weights agentic coder that just proved good enough to be the foundation of Cognition's SWE-2
- Claude Fable 5.1 (Anthropic) — the premium reasoning/coding flagship, the model other labs benchmark against
- GPT-5.6 Sol (OpenAI) — OpenAI's efficient frontier model, tuned for strong performance at moderate cost
From Cognition's own launch benchmarks for context: on FrontierCode 1.1 Main, Kimi K3 scores 44.2%, GPT-5.6 Sol 47.5%, and Fable 5.1 50.9%. On DeepSWE 1.1, K3 scores 68.5% vs Sol's 72.7% and Fable 5.1's 67.4%. Close enough that price should decide — so let's talk price.
The Pricing Table (Live From Qubax)
Prices pulled from the Qubax platform, per 1M tokens. "OpenRouter" is the standard list price elsewhere; Qubax prices reflect an open market where compute providers compete on price:
| Model | Qubax Input | Qubax Output | OpenRouter Input | OpenRouter Output | Your Savings (Output) |
|---|---|---|---|---|---|
| Kimi K3 | $0.67 | $2.69 | $2.34 | $11.70 | 77% |
| GPT-5.6 Sol | $0.25 | $0.99 | $1.00 | $5.00 | 80% |
| Claude Fable 5.1 | $5.99 | $29.97 | $10.00 | $50.00 | 40% |
Round 1: For Coding — SWE-2's Base vs the Frontier
Winner: GPT-5.6 Sol (with an asterisk)
On raw agentic-coding benchmarks, these three are remarkably close:
| Benchmark | Kimi K3 | GPT-5.6 Sol | Claude Fable 5.1 |
|---|---|---|---|
| FrontierCode 1.1 Main | 44.2% | 47.5% | 50.9% |
| DeepSWE 1.1 | 68.5% | 72.7% | 67.4% |
| Terminal-Bench 2.1 | 88.3% | 88.8% | 91.4% |
| Terminal-Bench 4 | 21.5% | 37.3% | 55.8% |
Fable 5.1 leads on the most respected coding evals. Sol wins DeepSWE. K3 trails on every benchmark — but never by more than ~6 points on the mid-tier evals, and Cognition's RL recipe just demonstrated those 5-6 points are recoverable with post-training.
The asterisk: on Terminal-Bench 4 — the hardest, least-saturated eval — the gap is brutal. Fable 5.1 scores 55.8%, more than double K3's 21.5%. For long-horizon autonomous tasks where the agent runs for hours unsupervised, Fable is in a different league. For supervised feature work and refactors, the gap mostly vanishes.
Round 2: For Cost Efficiency — It's Not Even Close
Winner: GPT-5.6 Sol, with Kimi K3 the value pick for open-weights needs
Run the actual math on a realistic agentic coding workload — 100K input tokens and 20K output tokens per task, 500 tasks/month:
| Model | Cost per Task | Monthly (500 tasks) |
|---|---|---|
| Kimi K3 at OpenRouter | $0.90 | $451 |
| Kimi K3 on Qubax | $0.12 | $61 |
| GPT-5.6 Sol at OpenRouter | $0.35 | $175 |
| GPT-5.6 Sol on Qubax | $0.045 | $22 |
| Claude Fable 5.1 at OpenRouter | $2.00 | $998 |
| Claude Fable 5.1 on Qubax | $1.20 | $598 |
Fable 5.1 delivers ~1.4x Sol's FrontierCode score for 27x the Qubax price per task. Unless your tasks are precisely the long-horizon kind where Terminal-Bench 4 matters, that premium is hard to justify. Sol is the efficiency champion; K3 on Qubax is jaw-dropping value if you want open-weights flexibility (self-hosting options, fine-tuning rights, no vendor lock-in).
Round 3: For Reasoning and Writing
Winner: Claude Fable 5.1
Outside agentic coding, the picture shifts. Fable 5.1 is Anthropic's flagship reasoning line, and it shows in multi-step analysis, nuanced instruction following, and long-document work. Kimi K3 is a coding-first model — its prose is competent but utilitarian, and it doesn't have Fable's knack for structured argumentation. GPT-5.6 Sol sits in the middle: strong general reasoning, better writing than K3, not Fable's equal on the hardest analytical tasks.
If your workload is "reason about this architecture and write a design doc," Fable's premium starts making sense. If it's "implement the tickets," it doesn't.
Round 4: Ecosystem and Flexibility
Winner: Kimi K3
- Kimi K3: open weights. You can fine-tune it, self-host it, inspect it — and build on it. Cognition's SWE-2 is the existence proof that K3 + strong post-training competes with closed frontier models. If your team has ML capability, K3 is the only one of the three you can own.
- GPT-5.6 Sol: closed API, but excellent tooling, mature SDK ecosystem, and available on every major aggregator.
- Claude Fable 5.1: closed API, premium positioning, deepest ecosystem of agent-framework integrations.
The Verdict
| Use Case | Winner | Why |
|---|---|---|
| Supervised coding (features, refactors, tests) | GPT-5.6 Sol | Near-frontier scores at 4% of Fable's task cost |
| Long-horizon autonomous agents | Claude Fable 5.1 | Terminal-Bench 4 gap (55.8% vs 37.3% vs 21.5%) is decisive |
| Open-weights / self-host / fine-tune | Kimi K3 | Only ownable model; proven frontier-adjacent with post-training |
| Reasoning & writing | Claude Fable 5.1 | Flagship reasoning quality, if you'll pay for it |
| Raw cost efficiency | GPT-5.6 Sol | $22/month vs $598 for the same workload |
The big picture: Cognition choosing Kimi K3 as SWE-2's base is the loudest possible signal that the gap between open-weights bases and closed frontier models is now a post-training problem, not a capability problem. The base models are winning; what you pay for at the top is the last 10-20% on the hardest tasks.
Try the Head-to-Head Yourself
Benchmarks are one thing; your codebase is another. Run the same prompt through all three on Qubax and compare outputs and cost in real time:
- Kimi K3 — from $0.67/$2.69 per 1M tokens on Qubax (77% off OpenRouter)
- GPT-5.6 Sol — from $0.25/$0.99 per 1M tokens on Qubax (80% off OpenRouter)
- Claude Fable 5.1 — from $5.99/$29.97 per 1M tokens on Qubax (40% off OpenRouter)
Try all three models on Qubax → [qubax.ai/models](https://qubax.ai/models)
FAQ
How much cheaper is Kimi K3 than Claude Fable 5.1 on Qubax?
Dramatically. K3 runs $0.67 input / $2.69 output per 1M tokens on Qubax versus Fable 5.1's $5.99 / $29.97 — roughly 9x cheaper on input and 11x cheaper on output, before considering that K3's Qubax price is already 77% below its OpenRouter rate.
Is GPT-5.6 Sol better than Claude Fable 5.1 for coding?
Depends on the task. Fable 5.1 leads on FrontierCode 1.1 Main (50.9% vs 47.5%) and Terminal-Bench 2.1 (91.4% vs 88.8%), and dominates the hardest Terminal-Bench 4 eval (55.8% vs 37.3%). GPT-5.6 Sol wins DeepSWE 1.1 (72.7% vs 67.4%) and delivers those scores at a small fraction of the price. For most day-to-day coding, Sol's value is unbeatable; for long autonomous runs, Fable leads.
Why did Cognition build SWE-2 on Kimi K3?
Cognition post-trained SWE-2 from Kimi K3's 2.8T-parameter base because K3 already had strong agentic-coding RL, and Cognition's training recipe added another 5-6 points on many benchmarks. The result scores within a point of Fable 5.1 on FrontierCode at 64% less cost — evidence that strong open bases plus good post-training rival closed frontier models.
Can I fine-tune Kimi K3 myself?
Yes — K3 is released with open weights, so you can fine-tune or self-host it depending on the access tier you use. That's a key differentiator versus GPT-5.6 Sol and Fable 5.1, which are API-only.
Where can I compare these models' prices live?
On qubax.ai/models — pricing is updated continuously, and because Qubax is an open market where compute providers compete on price, rates frequently sit well below OpenRouter prices.
