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Real head-to-head · same prompt, one shot

Qwen 3.8 vs Kimi K2.7 · Fast

Alibaba's 2.4T flagship — benched through Qoder. vs Fast mode — top speed, minimal thinking.

Qwen 3.8 · contextQoder-hosted
Kimi K2.7 · Fast · context256K tokens
Qwen 3.8 · priceQoder plan
Kimi K2.7 · Fast · priceFlat plan (no per-token bill)
Qwen 3.8 · vendorAlibaba
Kimi K2.7 · Fast · vendorMoonshot AI

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 Qwen 3.8 and Kimi K2.7 · Fast, side by side, on 38 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.

Qwen 3.8 · Benched on GoldieBench via the Qoder CLI (`qoder-qwen`, model Qwen3.8-Max-Preview) — the only door while it has no public API. Non-game tasks are one-shot like the rest of the field. GAME tasks run in Qoder's real AGENT mode: skill-infused build, then up to 2 QA fix rounds where a vision judge + live console errors are fed back and Qwen 3.8 edits its own file (it took crypt from a black-screen 3.0 to a torch-lit 7.8). Scored on a mid-play frame by the same Opus judge as everyone else. This is a partial run — the full 50-task card replaces it when the batch completes.

Kimi K2.7 · Fast · Wired into Agent OS as the snappy default — first-pass attempts, agent chatter, live demos.

Side-by-side on 50 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 = 🥉).

Task ↓
Qwen 3.8
Kimi K2.7 · Fast
Game
Qwen 3.8 on Arcade
Kimi K2.7 · Fast on Arcade
Game
Qwen 3.8 on Crypt
Kimi K2.7 · Fast on Crypt
Game
Qwen 3.8 on Dogfight
Kimi K2.7 · Fast on Dogfight
Game
Qwen 3.8 on Doom
Kimi K2.7 · Fast on Doom
Qwen 3.8 on Dragonflight
Kimi K2.7 · Fast on Dragonflight
Qwen 3.8 on Dragonrealm
Kimi K2.7 · Fast on Dragonrealm
Game
🥈Qwen 3.8 on Flightsim
Kimi K2.7 · Fast on Flightsim
Game
Qwen 3.8 on Game
Kimi K2.7 · Fast on Game
Game
🥈Qwen 3.8 on Gtadrive
Kimi K2.7 · Fast on Gtadrive
Game
🥉Qwen 3.8 on Gtafoot
Kimi K2.7 · Fast on Gtafoot
🥈Qwen 3.8 on Neonblaster
Kimi K2.7 · Fast on Neonblaster
Game
Qwen 3.8 on Neonracer
Kimi K2.7 · Fast on Neonracer
Qwen 3.8 on Nordiccrypt
Kimi K2.7 · Fast on Nordiccrypt
Game
🥇Qwen 3.8 on Outrun
Kimi K2.7 · Fast on Outrun
Game
🥉Qwen 3.8 on Racing
Kimi K2.7 · Fast on Racing
Game
Qwen 3.8 on Rpg
Kimi K2.7 · Fast on Rpg
Game
🥉Qwen 3.8 on Skyrim
Kimi K2.7 · Fast on Skyrim
Qwen 3.8 on Twilightvale
Kimi K2.7 · Fast on Twilightvale
Page
🥇Qwen 3.8 on Aipbpromo
Kimi K2.7 · Fast on Aipbpromo
Page
Qwen 3.8 on Landing
Kimi K2.7 · Fast on Landing
Sim
Qwen 3.8 on Blackhole
Kimi K2.7 · Fast on Blackhole
Sim
🥇Qwen 3.8 on Boids
Kimi K2.7 · Fast on Boids
Sim
🥇Qwen 3.8 on Cloth
Kimi K2.7 · Fast on Cloth
Sim
Qwen 3.8 on Fluid
Kimi K2.7 · Fast on Fluid

Strengths & weaknesses I logged

Qwen 3.8

Strengths

  • Skyrim-style open worlds — the Dragon Realm build rendered a lit snowfield, first-person sword and working roaming enemies (7.8)
  • Held up across game genres early — voxel sandbox and Doom raycaster both came out shippable
  • Runs as a real agentic coder inside Qoder (writes + iterates on files), not just a chat model

Trade-offs

  • Torch-lit dungeon (crypt) came out generic (6.3); one open-world RPG one-shot black-screened (twilightvale 2.5) — classic three.js r128 API drift
  • Preview is Qoder / Token-Plan only — no OpenRouter or public API, so it can't be routed into an app the way the OpenRouter models can

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 Qwen 3.8 Kimi K2.7 · Fast
VendorAlibabaMoonshot AI
Context windowServed through Alibaba's Qoder agent platform; the 3.8-Max preview has no standalone public context window yet.256,000 tokens
PriceQoder planFlat plan (no per-token bill)
Pricing detailQwen3.8-Max-Preview is Alibaba's ~2.4T-parameter flagship, positioned just behind Claude Fable 5. It is NOT on OpenRouter or a public API yet — the only access today is inside Qoder (Alibaba's agentic coding platform, free 2-week Pro trial). Benched here via the Qoder CLI on model `Qwen3.8-Max-Preview`, one-shot.Same flat-rate plan as standard Kimi K2.7 — Fast mode is a runtime toggle, not a separate model. Vendor: Moonshot AI (moonshot.ai).
Release2026-072026-06
Bench coverage41/41 scored · avg 8.22/100/47 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 Qwen 3.8 and Kimi K2.7 · Fast both into the Agent Operating System and dispatch each from the kanban by task type — one-shot 3d game and world prototypes where atmosphere matters → Qwen 3.8, snappy iteration inside agent loops → Kimi K2.7 · Fast. That's the same setup I run for the 4,000+ founders inside the AI Profit Boardroom.

FAQ — Qwen 3.8 vs Kimi K2.7 · Fast

Which is better, Qwen 3.8 or Kimi K2.7 · Fast?

On Goldie Bench, Qwen 3.8 averages no scored verdicts yet across the shared tasks, with 10 gold, 9 silver, 5 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 Qwen 3.8 cost vs Kimi K2.7 · Fast?

Qwen 3.8: Qwen3.8-Max-Preview is Alibaba's ~2.4T-parameter flagship, positioned just behind Claude Fable 5. It is NOT on OpenRouter or a public API yet — the only access today is inside Qoder (Alibaba's agentic coding platform, free 2-week Pro trial). Benched here via the Qoder CLI on model `Qwen3.8-Max-Preview`, one-shot. Kimi K2.7 · Fast: Same flat-rate plan as standard Kimi K2.7 — Fast mode is a runtime toggle, not a separate model. Vendor: Moonshot AI (moonshot.ai).

What's the context window for Qwen 3.8 vs Kimi K2.7 · Fast?

Qwen 3.8 has a Served through Alibaba's Qoder agent platform; the 3.8-Max preview has no standalone public context window yet. context window. Kimi K2.7 · Fast has a 256,000 tokens context window.

When should I pick Qwen 3.8 over Kimi K2.7 · Fast?

Pick Qwen 3.8 for: One-shot 3D game and world prototypes where atmosphere matters; Anyone already in the Qoder IDE/CLI wanting a near-frontier model free on the Pro trial; A cheaper stand-in for Fable 5 on creative-visual builds. The trade-off is the weaknesses we logged on the bench: Torch-lit dungeon (crypt) came out generic (6.3); one open-world RPG one-shot black-screened (twilightvale 2.5) — classic three.js r128 API drift; Preview is Qoder / Token-Plan only — no OpenRouter or public API, so it can't be routed into an app the way the OpenRouter models can.

When should I pick Kimi K2.7 · Fast over Qwen 3.8?

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 Qwen 3.8 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.

The same stack Julian uses

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 4,000+ founders shipping with it every day all live inside the AI Profit Boardroom.

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