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

Claude Sonnet 5 vs Qwen 3.7

The agentic SWE frontier — 82% SWE-bench Verified, Dev Team mode. vs Multilingual open-weights — strong on Chinese reasoning.

Head-to-head verdict: Claude Sonnet 5 wins 31–11.

Claude Sonnet 5 · context1M tokens
Qwen 3.7 · context256K tokens
Claude Sonnet 5 · price$3 / $15 per M ($2/$10 intro)
Qwen 3.7 · priceOpen weights · free for individuals
Claude Sonnet 5 · vendorAnthropic
Qwen 3.7 · vendorAlibaba

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 Claude Sonnet 5 and Qwen 3.7, side by side, on 42 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.

Claude Sonnet 5 · Reach for it in Agent OS when the job is iterative, tool-using software engineering. For one-shot visual builds, GLM 5.2 (free) beat it 4-1 here.

Qwen 3.7 · Wired alongside GLM-5.2 in Agent OS for open-weights agent loops where you want vendor diversity.

Side-by-side on 42 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 ↓
Claude Sonnet 5
Qwen 3.7
Game
Claude Sonnet 5 on Arcade
Qwen 3.7 on Arcade
Game
Claude Sonnet 5 on Crypt
Qwen 3.7 on Crypt
Game
Claude Sonnet 5 on Dogfight
Qwen 3.7 on Dogfight
Game
Claude Sonnet 5 on Doom
Qwen 3.7 on Doom
Claude Sonnet 5 on Dragonflight
Qwen 3.7 on Dragonflight
Claude Sonnet 5 on Dragonrealm
Qwen 3.7 on Dragonrealm
Game
Claude Sonnet 5 on Game
Qwen 3.7 on Game
Claude Sonnet 5 on Neonblaster
Qwen 3.7 on Neonblaster
Game
Claude Sonnet 5 on Neoncity
Qwen 3.7 on Neoncity
Game
🥈Claude Sonnet 5 on Neonracer
Qwen 3.7 on Neonracer
Claude Sonnet 5 on Nordiccrypt
Qwen 3.7 on Nordiccrypt
Game
🥇Claude Sonnet 5 on Outrun
Qwen 3.7 on Outrun
Game
🥈Claude Sonnet 5 on Pool
Qwen 3.7 on Pool
Game
Claude Sonnet 5 on Racing
Qwen 3.7 on Racing
Game
Claude Sonnet 5 on Raycaster
Qwen 3.7 on Raycaster
Game
Claude Sonnet 5 on Rpg
Qwen 3.7 on Rpg
Game
Claude Sonnet 5 on Skyrim
Qwen 3.7 on Skyrim
Claude Sonnet 5 on Twilightvale
Qwen 3.7 on Twilightvale
Game
Claude Sonnet 5 on Voxelcraft
Qwen 3.7 on Voxelcraft
Page
Claude Sonnet 5 on Landing
Qwen 3.7 on Landing
Page
Claude Sonnet 5 on Webos
Qwen 3.7 on Webos
Sim
Claude Sonnet 5 on Blackhole
Qwen 3.7 on Blackhole
Sim
Claude Sonnet 5 on Boids
Qwen 3.7 on Boids
Sim
Claude Sonnet 5 on Cloth
Qwen 3.7 on Cloth

Where Claude Sonnet 5 beat Qwen 3.7

The tasks where I gave Claude Sonnet 5 a higher 0–10 score on the same prompt — with the actual commentary from my source guides.

Raycaster Game
Claude Sonnet 5 8.0 · Qwen 3.7 4.0 (+4.0)

What I saw: Strong, shippable 3D maze: clean rendered walls with lighting/shadows, checkerboard floor, working minimap with player+goal markers, and solid controls/UI. Uses real 3D geometry rather than classic raycasting and looks a bit flat/plain (colored walls without texture), keeping it …

Claude Sonnet 5 8.4 · Qwen 3.7 5.0 (+3.4) · GPU Turing patterns

What I saw: Strong GPU Gray-Scott sim rendering clean cell/worm Turing structures with a polished glassy control panel, presets, and interactive seeding; slight weakness is somewhat uniform blob patterns rather than more dramatic branching coral, keeping it just under the top.

Outrun Game
Claude Sonnet 5 8.6 · Qwen 3.7 5.5 (+3.1) · Textbook synthwave outrun

What I saw: Gorgeous, on-brief execution — striped retro sun, parallax mountains, glowing pink/cyan rumble strips and lane markers on a proper pseudo-3D road, plus a detailed neon car and polished CRT scanline/vignette overlays. Speed reads 000 in the shot (idle), but the classic Jake-Gordon…

Galaxy Sim
Claude Sonnet 5 8.6 · Qwen 3.7 6.0 (+2.6) · gorgeous spiral swirl

What I saw: Beautiful multi-arm spiral with convincing color gradient (warm core to violet edges), bright glowing bulge, and background starfield—clearly on-brief and polished. Full swirl/orbit/zoom interactivity with a mouse-influence vortex on the particles makes this a task winner.

Synthwave Visual
Claude Sonnet 5 8.4 · Qwen 3.7 6.0 (+2.4)

What I saw: Gorgeous, on-brief synthwave scene with striped sun, layered mountains, glowing neon title and a warm-to-purple gradient grid that reads beautifully; only knock is a visible rectangular artifact around the sun (the sky plane/glow seam) that slightly breaks the polish.

Where Qwen 3.7 beat Claude Sonnet 5

The tasks where I gave Qwen 3.7 a higher 0–10 score on the same prompt — with the actual commentary from my source guides.

Solar Sim
Qwen 3.7 8.0 · Claude Sonnet 5 2.5 (+5.5)

What I saw: 7KB · plays clean · webgl, controls, rAF

Aurora Visual
Qwen 3.7 7.5 · Claude Sonnet 5 2.5 (+5.0)

What I saw: 6KB · plays clean · webgl, rAF

Wormhole Sim
Qwen 3.7 8.0 · Claude Sonnet 5 3.0 (+5.0)

What I saw: 7KB · plays clean · webgl, input, rAF

Qwen 3.7 7.5 · Claude Sonnet 5 3.0 (+4.5)

What I saw: 25KB · plays clean · plain

Orbit Sim
Qwen 3.7 7.5 · Claude Sonnet 5 3.5 (+4.0)

What I saw: Opus nailed the brief — distinct labelled planet orbits, a real NEO panel, a sim clock. GLM went dramatic with a glowing nebula swirl (gorgeous, but more galaxy than orbit map). Qwen drew a dense, busy orbital swarm — structurally orbit-like but dimmer and harder to read.

Strengths & weaknesses I logged

Claude Sonnet 5

Strengths

  • 82.1% SWE-bench Verified — first model past 80% on real GitHub-issue repair
  • Dev Team multi-agent mode + 1M context for repo-level agentic work
  • Precision on hard logic — won the raycaster the open-weight field kept botching

Trade-offs

  • One-shot creative-visual builds trail GLM 5.2 here (lost 4 of 5) — no iteration to catch its own bugs
  • A temporal-dead-zone bug blanked its N-body orbit sim on the first shot

Qwen 3.7

Strengths

  • Open weights, free for individuals — same model class as GLM-5.2
  • Best-of-three on fluid simulation in the Goldie Bench bench
  • Multilingual depth — Chinese reasoning especially strong

Trade-offs

  • Only 5 tasks scored on the bench so far — small sample size
  • Trails GLM-5.2 on cinematic visual builds at similar pricing

Pricing & context — the spec sheet

Spec Claude Sonnet 5 Qwen 3.7
VendorAnthropicAlibaba
Context window1,000,000 tokens256,000 tokens
Price$3 / $15 per M ($2/$10 intro)Open weights · free for individuals
Pricing detail$3.00 input / $15.00 output per million tokens; introductory $2.00/$10.00 through 2026-08-31.Alibaba's open-weights release — downloadable from Hugging Face, runnable locally or via Alibaba Cloud's free tier for individuals.
Release2026-06-302026-06
Bench coverage42/42 scored · avg 7.18/1042/42 scored · avg 6.93/10

The verdict — which should you pick?

Across 42 scored shared tasks, the averages are essentially tied — Claude Sonnet 5 7.18 vs Qwen 3.7 6.93. This isn't the comparison where one wins; it's the comparison where you pick based on context, pricing, and what you're actually trying to ship.

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 Claude Sonnet 5 and Qwen 3.7 both into the Agent Operating System and dispatch each from the kanban by task type — agentic software engineering — write / run / test / fix loops on real repos → Claude Sonnet 5, open-weights alternative to glm-5.2 when you want a different model family → Qwen 3.7. That's the same setup I run for the 3,600+ founders inside the AI Profit Boardroom.

FAQ — Claude Sonnet 5 vs Qwen 3.7

Which is better, Claude Sonnet 5 or Qwen 3.7?

On Goldie Bench, Claude Sonnet 5 averages 7.18/10 across the shared tasks, with 3 gold, 3 silver, 3 bronze overall. Qwen 3.7 averages 6.93/10, with 0 gold, 0 silver, 0 bronze. Claude Sonnet 5 wins the head-to-head 31–11.

How much does Claude Sonnet 5 cost vs Qwen 3.7?

Claude Sonnet 5: $3.00 input / $15.00 output per million tokens; introductory $2.00/$10.00 through 2026-08-31. Qwen 3.7: Alibaba's open-weights release — downloadable from Hugging Face, runnable locally or via Alibaba Cloud's free tier for individuals.

What's the context window for Claude Sonnet 5 vs Qwen 3.7?

Claude Sonnet 5 has a 1,000,000 tokens context window. Qwen 3.7 has a 256,000 tokens context window.

When should I pick Claude Sonnet 5 over Qwen 3.7?

Pick Claude Sonnet 5 for: Agentic software engineering — write / run / test / fix loops on real repos; Repo-level reasoning across a 1M-token context (Dev Team multi-agent mode); Precise logic — raycasters, physics — where one-shot open models slip. The trade-off is the weaknesses we logged on the bench: One-shot creative-visual builds trail GLM 5.2 here (lost 4 of 5) — no iteration to catch its own bugs; A temporal-dead-zone bug blanked its N-body orbit sim on the first shot.

When should I pick Qwen 3.7 over Claude Sonnet 5?

Pick Qwen 3.7 for: Open-weights alternative to GLM-5.2 when you want a different model family; Multilingual workloads (Chinese, multi-script content); Fluid and particle simulations. The trade-off is the weaknesses we logged on the bench: Only 5 tasks scored on the bench so far — small sample size; Trails GLM-5.2 on cinematic visual builds at similar pricing.

How does Goldie Bench score Claude Sonnet 5 vs Qwen 3.7?

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 3,600+ founders shipping with it every day all live inside the AI Profit Boardroom.

3,600+founders
258documented wins
38countries
$59/momonthly