
Opus 4.8 vs Kimi K2.7 · Fast
The reasoning king — deepest thinking, premium price. vs Fast mode — top speed, minimal thinking.
What I tested — same prompt, two models
I run the same fixed prompt set through every new model the day it drops — same string, one shot, single HTML file out — and I score the result 0–10 on whether it ran, how close it hit the brief, and how good it looked. Below is what came out when I gave the exact same prompts to Opus 4.8 and Kimi K2.7 · Fast, side by side, on 2 shared tasks inside the Agent Operating System.
Both models were given identical prompts inside the Agent Operating System — no help, no iteration, no "best of N" tricks. I run each prompt once, save the HTML file the model produces, and score it 0–10 on whether it ran, how close it hit the brief, and how good it looked. The scoring is mine. The verdicts below are pulled from my source comparison guides at agentos.guide where I publish every score and the reasoning behind it.
Opus 4.8 · The default when the build has to ship on the first prompt — Opus is the safety net inside Agent OS for hard one-shots.
Kimi K2.7 · Fast · Wired into Agent OS as the snappy default — first-pass attempts, agent chatter, live demos.
Side-by-side on 18 shared tasks
Click any cell to play that model's actual one-shot attempt. Medals are derived from my 0–10 scores per task (highest = 🥇, second = 🥈, third = 🥉).
Strengths & weaknesses I logged
Opus 4.8
Strengths
- Most consistent across the Goldie Bench bench — no weak build, 8.46/10 average
- Deepest one-shot reasoning, especially on game-feel and physics
- Extended thinking mode handles up to 1M tokens of context
Trade-offs
- 5–10× the per-token cost of every other model on the bench
- Less flair on cinematic visuals than GLM-5.2 — playing it safer wins on accuracy, costs you on showpiece moments
Kimi K2.7 · Fast
Strengths
- Lowest latency of the three Kimi modes for short builds
- Same 256K context as Quality mode
- Best when you need agent-loop responsiveness over polish
Trade-offs
- Skips deeper reasoning passes — bronze-tier on tasks needing planning
- Julian explicitly does not assign scores to Kimi modes on the standalone bench
Pricing & context — the spec sheet
| Spec | Opus 4.8 | Kimi K2.7 · Fast |
|---|---|---|
| Vendor | Anthropic | Moonshot AI |
| Context window | 200,000 tokens (1M with extended thinking) | 256,000 tokens |
| Price | $15 / $75 per M tokens | Flat plan (no per-token bill) |
| Pricing detail | Premium pricing via the Anthropic API: $15 per million input tokens, $75 per million output tokens. Extended thinking is included but adds latency. | Same flat-rate plan as standard Kimi K2.7 — Fast mode is a runtime toggle, not a separate model. |
| Release | 2026-05 | 2026-06 |
| Bench coverage | 13/17 scored · avg 8.46/10 | 0/3 scored · avg — |
The verdict — which should you pick?
Not enough scored shared tasks yet for a head-to-head average. The live demos for both are on the matrix above — play them and form your own opinion.
If you only run one of these inside your stack, the head-to-head average above is the call. If you can run both, my honest play is to wire Opus 4.8 and Kimi K2.7 · Fast both into the Agent Operating System and dispatch each from the kanban by task type — mission-critical one-shot builds where 'has to work the first time' matters → Opus 4.8, snappy iteration inside agent loops → Kimi K2.7 · Fast. That's the same setup I run for the 3,600+ founders inside the AI Profit Boardroom.
FAQ — Opus 4.8 vs Kimi K2.7 · Fast
Which is better, Opus 4.8 or Kimi K2.7 · Fast?
On Goldie Bench, Opus 4.8 averages no scored verdicts yet across the shared tasks, with 8 gold, 5 silver, 0 bronze overall. Kimi K2.7 · Fast averages no scored verdicts yet, with 0 gold, 0 silver, 0 bronze. Not enough scored shared tasks yet to call a winner.
How much does Opus 4.8 cost vs Kimi K2.7 · Fast?
Opus 4.8: Premium pricing via the Anthropic API: $15 per million input tokens, $75 per million output tokens. Extended thinking is included but adds latency. Kimi K2.7 · Fast: Same flat-rate plan as standard Kimi K2.7 — Fast mode is a runtime toggle, not a separate model.
What's the context window for Opus 4.8 vs Kimi K2.7 · Fast?
Opus 4.8 has a 200,000 tokens (1M with extended thinking) context window. Kimi K2.7 · Fast has a 256,000 tokens context window.
When should I pick Opus 4.8 over Kimi K2.7 · Fast?
Pick Opus 4.8 for: Mission-critical one-shot builds where 'has to work the first time' matters; Hard reasoning tasks (planning, multi-step) where you'll pay for the depth; Anything where vendor reliability beats the per-token bill. The trade-off is the weaknesses we logged on the bench: 5–10× the per-token cost of every other model on the bench; Less flair on cinematic visuals than GLM-5.2 — playing it safer wins on accuracy, costs you on showpiece moments.
When should I pick Kimi K2.7 · Fast over Opus 4.8?
Pick Kimi K2.7 · Fast for: Snappy iteration inside agent loops; Short prompts where Quality mode would over-think; Live demos where latency matters more than the last 5% of polish. The trade-off is the weaknesses we logged on the bench: Skips deeper reasoning passes — bronze-tier on tasks needing planning; Julian explicitly does not assign scores to Kimi modes on the standalone bench.
How does Goldie Bench score Opus 4.8 vs Kimi K2.7 · Fast?
Every demo on this page was built by Julian Goldie inside the Agent Operating System — same fixed prompt for both models, one shot, single HTML file out. Each result gets a 0–10 score on whether it ran, how close it hit the brief, and how good it looked. The highest score on each task gets gold; second gets silver; third gets bronze. See methodology for full provenance.
Related comparisons
Other head-to-heads using the same scoring system:
Opus 4.8 vs GLM-5.2 Kimi K2.7 · Fast vs GLM-5.2 Opus 4.8 vs Qwen 3.7 Kimi K2.7 · Fast vs Qwen 3.7 Opus 4.8 vs Kimi K2.7 Kimi K2.7 · Fast vs Kimi K2.7Full model pages: Opus 4.8 · Kimi K2.7 · Fast · back to the leaderboard
Run this stack yourself.
Every demo on this bench was built inside the Agent Operating System — one prompt, one shot, single HTML file out. The Agent OS, the prompts, the templates, the weekly walkthroughs and 3,600+ founders shipping with it every day all live inside the AI Profit Boardroom.


















