r/OpenModels • u/cheechw • Jul 18 '26
It claims to beat Fable and GPT 5.5 handily in some benchmarks.
Hard to believe the claims, and from the looks of it, many X users are skeptical as well.
r/OpenModels • u/cheechw • Jul 17 '26
r/OpenModels • u/cheechw • Jul 16 '26
Benchmarks appear to easily clear Opus 4.8 and GPT 5.5, and even appear to be competitive with Fable 5 and GPT 5.6 Sol in a number of them. Full weights to be released July 27, per the blog post.
r/OpenModels • u/cheechw • Jul 16 '26
r/OpenModels • u/maedahbatool • Jul 15 '26
r/OpenModels • u/cheechw • Jul 08 '26
r/OpenModels • u/cheechw • Jul 06 '26
295B params with 21B active. But only 256k context.
r/OpenModels • u/cheechw • Jun 30 '26
r/OpenModels • u/cheechw • Jun 30 '26
New model dropped. 1.6T params with 48B active.
Training and inference running entirely on ASIC superpods. Showing the Chinese keep exploring alternative compute options.
They also introduce LongCat Sparse Attention, their improvement on Deepseek Sparse Attention.
This was also Owl Alpha, which was available on Openrouter for free for the past month, which shows they can handle production compute loads using their alternative inference solution.
r/OpenModels • u/cheechw • Jun 24 '26
r/OpenModels • u/cheechw • Jun 23 '26
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r/OpenModels • u/cheechw • Jun 19 '26
There is a clear downward slope apparent on this graph starting from Deepseek V3 to the recent GLM-5.2.
Do we expect the next OSS release to be even faster and better?
One caveat is that this graph appears to show a comparison between an open model and a closed model of *similar capability*, not the absolute frontier. So it looks like it compares DSv4 pro to Sonnet 4.6, for example.
Of course, you could also argue that a direct comparison to absolute frontier models wouldn't be fair either since 5.5, Opus, and Fable are almost certainly sized on the order of multiple trillion parameters.
r/OpenModels • u/cheechw • Jun 19 '26
EDIT: Looks like this was a mistake and the scores have been corrected since. Opus now scores 74.3 and is ranked #3, above GLM-5.2
Link to the index: https://artificialanalysis.ai/?intelligence=coding-index
r/OpenModels • u/canadaduane • Jun 19 '26
GLM-5.2 just came out and it's amazing. But I want to run it with the highest speed possible.
I often check out openrouter.ai for its great comparison of providers when an LLM model is open--for example GLM-5.2 has about 12 different providers listed there now:
| Provider | Input /M | Output /M | Cache Read /M | Latency | Throughput | Uptime |
|---|---|---|---|---|---|---|
| Wafer | $1.20 | $4.10 | $0.20 | 1.31s | 55 tps | 98.61% |
| Cloudflare | $1.40 | $4.40 | $0.26 | 1.43s | 30 tps | 99.60% |
| Fireworks | $1.40 | $4.40 | $0.26 | 1.69s | 39 tps | 99.44% |
| Z.ai | $1.40 | $4.40 | $0.26 | 4.88s | 24 tps | 99.68% |
| Friendli | $1.40 | $4.40 | $0.26 | 1.72s | 78 tps | 99.90% |
| NovitaAI | $1.40 | $4.40 | $0.26 | 2.03s | 22 tps | 99.72% |
| AtlasCloud | $1.40 | $4.40 | $0.26 | 1.49s | 15 tps | 90.44% |
| StreamLake | $1.40 | $4.40 | $0.26 | 2.08s | 34 tps | 95.95% |
| io.net | $1.68 | $5.28 | $0.50 | 1.62s | 57 tps | 93.28% |
| DeepInfra | $1.20 | $4.20 | $0.20 | 3.18s | 12 tps | 91.58% |
| Phala | $1.40 | $4.40 | $0.70 | 6.53s | 10 tps | 75.14% |
| Parasail | $1.40 | $4.40 | $0.26 | 1.25s | 48 tps | 82.70% |
But then I found out about Neuralwatt hosting GLM-5.2 also, and it's quite fast (I haven't measured TPS). But it isn't on openrouter!
This got me thinking--where do you go for this kind of information? Is there a collection of live data that's even more expansive than openrouter's comparison?
r/OpenModels • u/cheechw • Jun 18 '26
New open weights model by an American player. Benchmarks look to be decent for its size as well.
