| type |
source_url |
author |
author_name |
posted |
engagement |
posted_by |
posted_by_name |
posted_by_id |
posted_in |
posted_in_topic |
posted_date |
tags |
| xpost |
https://x.com/atomic_chat_hq/status/2072446067962978411 |
@atomic_chat_hq |
atomic.chat |
2026-07-01 |
| likes |
reposts |
quotes |
replies |
bookmarks |
views |
| 4005 |
309 |
82 |
168 |
2028 |
1730000 |
|
@NetLightning |
Netbits ⚡️ Stachelbanane |
303303834 |
OME-Gruppe |
News & Infos |
2026-07-02 |
| xpost |
| coding-benchmark |
| fable5 |
| gpt-5.5 |
| opus-4.8 |
| glm-5.2 |
| price-performance |
| one-shot |
| html5-canvas |
| physics-simulation |
| chinese-models |
| cost-routing |
|
atomic.chat — Coding Benchmark: Fable 5 vs GPT 5.5 vs Opus 4.8 vs GLM 5.2
Original Post
Fable 5 crushed a coding contest, but cost 6x more than Opus 4.8.
4 models got the same prompt: build three self-contained HTML5 canvas scenes with real physics demos:
- A train derailing off a broken bridge into the water
- Two cars jumping off ramps and colliding mid-air over a canyon
- A monster truck crushing a row of parked cars
Results (One-Shot, Same Prompt)
| Model |
Tokens |
Cost |
Grade |
Notes |
| Fable 5 (Anthropic) |
62,158 |
$3.12 |
A+ |
Best quality, all three scenes |
| GPT 5.5 (OpenAI) |
37,753 |
$1.14 |
A− |
Close to Fable, beat it on monster truck scene |
| Opus 4.8 (Anthropic) |
22,280 |
$0.56 |
— |
(Grade not specified in post) |
| GLM 5.2 (Z.ai) |
36,246 |
$0.08 |
B+ |
Cheapest by far, competitive but didn't win any scene |
Cost-Performance Matrix
| Metric |
Fable 5 |
GPT 5.5 |
Opus 4.8 |
GLM 5.2 |
| Cost |
$3.12 |
$1.14 |
$0.56 |
$0.08 |
| Tokens |
62,158 |
37,753 |
22,280 |
36,246 |
| Cost per 1K tokens |
$0.050 |
$0.030 |
$0.025 |
$0.002 |
| vs Fable 5 cost |
1× |
2.7× cheaper |
5.6× cheaper |
39× cheaper |
| Quality grade |
A+ |
A− |
— |
B+ |
Key finding: GLM 5.2 is 39× cheaper than Fable 5 while remaining competitive (B+ grade). Opus 4.8 is 5.6× cheaper than Fable 5 with lowest token count.
Key Takeaways from Replies
| User |
Takeaway |
| @Krysoph |
GLM 5.2 could be better with more iterations + vision model assistance |
| @suzzvsworld |
"GLM at $0.08 and still competitive is the real story. Chinese models are making the price conversation impossible to ignore" |
| @rohanpaul_ai |
Quality scales with spend; would love to see test with strict max-token limit |
| @debugging_yami |
GPT 5.5 best value — nearly par with Fable at 1/3 cost |
Context Notes
- Test type: One-shot, same prompt, no iteration — measures raw generation quality per dollar
- Task domain: HTML5 Canvas physics simulations (derailing train, mid-air car collision, monster truck crushing)
- Engagement: 1.73M views, 4K likes, 2K bookmarks — viral resonance indicates market hunger for transparent cost-performance comparisons
- Narrative: Reinforces ../../wiki/concepts/llm/chinese-model-cost-routing.md thesis — Chinese models (GLM 5.2) make price-performance conversation impossible to ignore
- GLM 5.2 at $0.08: This is the hardest data point yet for the "39× cheaper" narrative. Previous benchmark: DeRonin's 87% cost-cut (5-12× per task). This is 39× on a single task.
Cross-References
External Links
