双 DGX Spark 用户实测：GLM 5.3 flash 性能提升 50% 以上
For dual DGX spark users; GLM 5.3 flash got a 50%+ performance boost
双 DGX Spark 用户实测显示，GLM 5.3 flash 在新版 recipe 下解码性能提升 50%-90%，解码速度已超过 DeepSeek v4.0 flash，仅 prefill 略有下降。
For the last few months, I ran DeepSeek v4.0 flash (NVFP4). First 0731, then visionexp because it was a free improvement. I got around 65 tps decode and almost 2k prefill, and ran 4-5 agents in parallel, totalling around 200 tps cumulative decode. Because of this, I did not feel like switching to GLM 5.3 because it would half the decode and prefill, did not scale well with multiple agents, and had a repetition bug a lot of people complained about.
Until a few days ago, when the latest version of this recipe dropped; a 50-90% decode improvement. So I took the plunge, and wow, am I impressed.
It's more intelligent than the new DeepSeek v4.1 flash (that does NOT run on dual DGX Sparks), and it's even faster than DeepSeek v4.0 flash in decode. Only a slight drop in prefill, which I'm more than happy to take in exchange;
| Test | visionexp-final (recorded) | glm53-low | Δ |
|---|---|---|---|
| B1 count-to-300 | 92.5 | 95.9 | +4% |
| B1 bulk SQL INSERT | 88.3 | 97.2 | +10% |
| B2 chat | 38.7 | 42.5 | +10% |
| B2 count | 92.8 | 96.0 | +3% |
| B2 code | 63.5 | 69.3 | +9% |
| B2 prose | 32.8 | 37.1 | +13% |
| B2 tool | 79.8 | 85.1 | +7% |
| B2 battery mean | 61.5 | 66.0 | +7% |
| B2 accepted tok/step | 3.26 of 6 (54%) | 3.55 of 8 (44%) | see note |
| B3 prefill @1.5K | 1738 | 1376 | -21% |
| B4 prefill @32K | 1902 | 1576 | -17% |
| B4 prefill @128K | 1758 | 1578 | -10% |
| B4 decode @32K | 41.1 | 44.2 | +7% |
| B4 decode @128K | 49.5 | 47.1 | -5% |
| B5 c1 aggregate | 91.7 | 90.1 | -2% |
| B5 c2 aggregate | 45.4 | 51.4 | +13% |
| B5 c4 aggregate | 63.4 | 58.6 | -7% |
| B5 c6 aggregate | 79.1 | 77.5 | -2% |
| B7 soak (40 min at c4) | 522 req, 0 err, 87.4 agg | 503 req, 0 err, 0 soft-empty, 83.6 agg | −4% |
| B8 byte-stable probes | 8/8 | 6/8 | worse |
| B8 garble gate | 30/30 clean | 30/30 clean | = |
| B8 non-Latin / U+FFFD | not measured | 3/3 clean, 0 U+FFFD | new gate |
| KV pool | 1,988,929 tok @ gmu 0.85 | 560,362 tok (6 GiB/rank pin) | −72% |
| NRestarts through the pass | 0 | 0 | = |
I've tested it for a few days now, both for technical coding, devops/sysadmin and also vision (to recognize some plants), and it is better than I hoped for. Basically Claude Opus 4.8 level. Slower of course because it has to think a lot more, but good enough to comfortably leave it chugging for hours on tickets without worry of derailing. I don't see a reason NOT to upgrade, so have a try and enjoy!
submitted by /u/swiebertjee
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来源：r/LocalLLaMA · reddit.com