
Real head-to-head · same prompt, one shot
Kimi K3 vs Hy3
Moonshot's 2.8T flagship — 1M context, tuned for long-horizon agent work. vs Tencent's open-weights coder — Apache-2.0, cheap, beats GLM-5.1 on frontend in Tencent's blind eval.
Head-to-head verdict: Kimi K3 wins 6–1.
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 Kimi K3 and Hy3, side by side, on 7 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.
Kimi K3 · Wired into the Agent OS as the `kimi-k3` Hermes profile and a K3 speed-toggle in the Kimi Code tab — used for long unattended agent runs where a slow-but-right model beats a fast-but-forgetful one.
Hy3 · Wired into the Agent OS as the 'Hy3 Coder' tab (chat + live preview + workspace) via OpenRouter. Bench built one-shot on the same prompts as the field; weak builds iterated by Hy3 itself (the model fixes its own builds).
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 = 🥉).
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Kimi K3
Hy3
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Where Kimi K3 beat Hy3
The tasks where I gave Kimi K3 a higher 0–10 score on the same prompt — with the actual commentary from my source guides.
Doom
Game
Kimi K3 8.0
·
Hy3 4.5
(+3.5)
What I saw: Strong, polished raycaster with detailed procedural lava/metal wall textures, minimap, HUD, gun sprite and a distant medkit pickup visible — very shippable DOOM atmosphere. Weak point: no monster is visible in the rendered frame and HP already at 91, so the core 'monsters chase y…
Dragonrealm
Game
Kimi K3 8.6
·
Hy3 7.2
(+1.4)
· atmospheric frozen realm
What I saw: Strong atmospheric render nails the Skyrim-style frozen night — moon, aurora, snowfall, drawn sword in-hand, glowing braziers, distant dragon silhouette on compass, and a full HUD with health/stamina bars. Polished lighting and moody vignette push it to the top of the field; mino…
Flightsim
Game
Kimi K3 8.2
·
Hy3 6.8
(+1.4)
What I saw: Strong, polished render with a clean 3D plane on a proper runway, full HUD (compass ribbon, artificial horizon, IAS/ALT gauges, throttle slider) and nice terrain/hangar/windsock props; minor blemish is the 'VS NaN' readout indicating an uninitialized vertical-speed calc, which ke…
Parachute
Game
Kimi K3 8.2
·
Hy3 6.8
(+1.4)
What I saw: Renders cleanly with a polished 3D scene—gradient sky, mountains, clouds, altitude bar, sink/wind stats, and a pulsing PULL button—clearly on-brief for freefall/steer/pull/land. Strong HUD and controls, but the jungle canopy reads as flat white/gray squares rather than dense gree…
Gtadrive
Game
Kimi K3 8.4
·
Hy3 7.4
(+1.0)
· neon night city
What I saw: Strong atmospheric render — cohesive dusk/neon skyline, lit facade textures, on-foot character with steal prompt, circular minimap with compass, and clean HUD all deliver the GTA sandbox brief. Loses a touch for a slightly empty foreground and unverified cop-chase/wanted mechanic…
Where Hy3 beat Kimi K3
The tasks where I gave Hy3 a higher 0–10 score on the same prompt — with the actual commentary from my source guides.
Aipbpromo
Page
Hy3 7.4
·
Kimi K3 6.5
(+0.9)
What I saw: Clean multi-scene pipeline with animated count-up stats, gold/cyan cinematic palette, particle field and progress bar render correctly; but the stats appear left-clustered and off-center with only two of four visible mid-animation, feeling sparse rather than composed, keeping it …
Strengths & weaknesses I logged
Kimi K3
Strengths
- Launch-day benchmarks put it around the Fable/Sol tier, with Terminal Bench (agentic terminal-driving) the standout
- 1M-token context verified on this bench's needle test: exact recall from 162k tokens of noise in 18s
- One-shot builds run long but land complete — its first bench game (13.4 min of thinking, 30,880 tokens) playtested with zero JS errors
- Included in the Kimi coding plan — frontier tier without a new bill
Trade-offs
- Slow on hard tasks — early testers report up to ~35 minutes at max reasoning; this bench saw 13+ minute single builds
- Launch-day rate limits on OpenRouter (429s) — the coding-plan endpoint was the reliable route
- Self-reports as K2.7 if you ask it — verify the served model via the API response, not the model's word
Hy3
Strengths
- Apache-2.0 open weights — self-host free, no lock-in
- Tencent's 270-expert blind eval: 2.67/4 vs GLM-5.1's 2.51, strongest on frontend / data / CI-CD
- Hallucination rate cut 12.5% → 5.4%; stable tool-calls across scaffoldings (<4% SWE-Bench variance)
Trade-offs
- Slow upstream on OpenRouter (30-90s per build) — fine for one-shots, sluggish for tight loops
- One-shot game builds can under-render (flat raycaster walls, unlit 3D) without an iterate pass
Pricing & context — the spec sheet
| Spec | Kimi K3 | Hy3 |
|---|---|---|
| Vendor | Moonshot AI | Tencent Hunyuan |
| Context window | 1,048,576 tokens — a full codebase in working memory | 262,144-token context window. Open weights (Apache-2.0) on HuggingFace / ModelScope / GitHub; benched here via OpenRouter. |
| Price | $3 / M in | $0.14 / 1M input · $0.58 / 1M output |
| Pricing detail | Launched July 16, 2026. 2.8T-param MoE (Moonshot's quickstart corrected the circulating 2.5T estimate). $3/M input on OpenRouter at launch; included at no extra cost in the Kimi coding plan (`k3` on the coding endpoint). | Tencent Hunyuan 3 — open-weights under Apache-2.0, so free to self-host. On OpenRouter it is one of the cheapest capable coders: ~$0.14/M in, $0.58/M out (1 RMB / 4 RMB). Upstream can be slow (30-90s to first token), but per-token cost is negligible. |
| Release | 2026-07-16 | 2026-07-06 |
| Bench coverage | 50/50 scored · avg 7.89/10 | 7/7 scored · avg 6.76/10 |
The verdict — which should you pick?
Across 7 scored shared tasks, Kimi K3 averaged 8.01/10, beating Hy3's 6.76/10 by 1.26 points. Pick Kimi K3 when the build has to ship on the first prompt and you can afford the trade-offs in the comparison below.
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 Kimi K3 and Hy3 both into the Agent Operating System and dispatch each from the kanban by task type — long-horizon agent runs → Kimi K3, cost-sensitive coding + frontend design where open weights matter → Hy3. That's the same setup I run for the 4,000+ founders inside the AI Profit Boardroom.
FAQ — Kimi K3 vs Hy3
Which is better, Kimi K3 or Hy3?
On Goldie Bench, Kimi K3 averages 8.01/10 across the shared tasks, with 8 gold, 4 silver, 7 bronze overall. Hy3 averages 6.76/10, with 0 gold, 0 silver, 0 bronze. Kimi K3 wins the head-to-head 6–1.
How much does Kimi K3 cost vs Hy3?
Kimi K3: Launched July 16, 2026. 2.8T-param MoE (Moonshot's quickstart corrected the circulating 2.5T estimate). $3/M input on OpenRouter at launch; included at no extra cost in the Kimi coding plan (`k3` on the coding endpoint). Hy3: Tencent Hunyuan 3 — open-weights under Apache-2.0, so free to self-host. On OpenRouter it is one of the cheapest capable coders: ~$0.14/M in, $0.58/M out (1 RMB / 4 RMB). Upstream can be slow (30-90s to first token), but per-token cost is negligible.
What's the context window for Kimi K3 vs Hy3?
Kimi K3 has a 1,048,576 tokens — a full codebase in working memory context window. Hy3 has a 262,144-token context window. Open weights (Apache-2.0) on HuggingFace / ModelScope / GitHub; benched here via OpenRouter. context window.
When should I pick Kimi K3 over Hy3?
Pick Kimi K3 for: long-horizon agent runs; whole-repo context work; terminal-driving agents. The trade-off is the weaknesses we logged on the bench: Slow on hard tasks — early testers report up to ~35 minutes at max reasoning; this bench saw 13+ minute single builds; Launch-day rate limits on OpenRouter (429s) — the coding-plan endpoint was the reliable route; Self-reports as K2.7 if you ask it — verify the served model via the API response, not the model's word.
When should I pick Hy3 over Kimi K3?
Pick Hy3 for: Cost-sensitive coding + frontend design where open weights matter; Self-hosters who want an Apache-2.0 model they fully own; Anyone wiring a cheap capable coder into a live build panel (Agent OS Hy3 Coder tab). The trade-off is the weaknesses we logged on the bench: Slow upstream on OpenRouter (30-90s per build) — fine for one-shots, sluggish for tight loops; One-shot game builds can under-render (flat raycaster walls, unlit 3D) without an iterate pass.
How does Goldie Bench score Kimi K3 vs Hy3?
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:
Kimi K3 vs Fusion Hy3 vs Fusion Kimi K3 vs Claude Opus 5 Hy3 vs Claude Opus 5 Kimi K3 vs Hermes MoA Hy3 vs Hermes MoA Kimi K3 vs GPT-5.6 Sol Hy3 vs GPT-5.6 SolFull model pages: Kimi K3 · Hy3 · back to the leaderboard
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.
4,000+founders
258documented wins
38countries
$59/momonthly





























