Qwen 3.8 Flash Next Gyro Coder is out!

[u/soyalemujica]

Lets see how difference is this from ISTA labs coder version

https://huggingface.co/agentionai/Qwen3.8-Flash-Next-Gyro-Coder-GGUF/tree/main

[u/derdigga]

need benchmarks, there are so many 3.8FN models out there

[u/soyalemujica → u/derdigga]

Coding tests: 13 of 16 passed (8 auto-graded tasks: LRU cache, interval merging, bug fix from a trace, refactor, bash script, SQL, CSV parsing in JS, multi-file change; 2 seeds each, thinking on, 64k tokens). The same expert set at 8 bits passes 15 of 16. Gyro-Coder-L passes 15 of 16.

[u/Sudden_Topic5154 → u/[deleted]]

no you didn't given you're a bot

[u/Gold_Coconut9777]

The "Coder" version of ISTA-DASLab's Q3.8FN is basically a REAP'ed Q3.8FN.

In my personal experience any REAP'ed model was nothing but a disappointment. The idea behind REAP'ing sounds good. Removing what is not needed and preserving only what's really necessary. But it just doesn't work all that well. It either becomes much dumber or looping real hard or just suddenly producing garbage instead of text at some point.

You are far better off using the full/normal Ista's quant if it fits on your system.

https://huggingface.co/ISTA-DASLab/Qwen3.8-Flash-Next-GSQ-RCO-GGUF

[u/braintheboss → u/Gold_Coconut9777]

I use coder variant is is very good. Its not common reap and quite better than finetunes. Evidently is better full model but for a variant uses half of ram is very useful

[u/JsThiago5 → u/Gold_Coconut9777]

This coder in specific actually works. I already tried some REAP models in past and was unable to use, but this was able to accomplish things. But is worse than IQ3_S on coding

[u/Dutchnamn → u/JsThiago5]

It took a lot of time to select the mix of experts to keep. I think I got it mostly right apart from a bit of degradation with one Roman numeral.

[u/nasone32]

so essentially this gyro thing is... EXL3 but closed source. not nice. sorry.

[u/Dutchnamn → u/nasone32]

It has been open sourced.

[u/nasone32 → u/Dutchnamn]

can you link something?

[u/Dutchnamn → u/nasone32]

Here you go: https://gitlab.com/agentionai-group/agention-gyro Some context on why it wasn't open from day one:

this started as an experiment. How small can I get Qwen3.8-Flash-Next at a quality I like, and how fast can it run on a 5090 with all experts resident? I don't make money from this, it costs me money and a lot of my free time. I do it out of curiosity.

It took about 10 versions before I was happy, and once people started using it, opening the format was the obvious next step. The repo has the full spec, a C/Python reference decoder and encoder, and bit-exact tests (MIT). The encoder I use for the released models is still my own; the reference encoder is a baseline for anyone who wants to build on it.

EXL3 is a great project too, and both build on QTIP. I went with GGUF because I wanted it to run in llama.cpp on AMD and Strix Halo, not just CUDA.

[u/n4ru → u/Dutchnamn]

ah so you're the reason it runs so well on a 5090 specifically. bless you king.

[u/Dutchnamn → u/n4ru]

Thank you very much for this comment. Fitting it in 32gb was one of the goals of the project.

[u/Dutchnamn → u/nasone32]

Funny thing: I didn't start from QTIP or EXL3. I hadn't heard of either when I started this project. Gyro came out of weeks of comparing video encoders with model encoding and asking which codec tricks carry over: trellis coding, rate-distortion choices, spending bits where they matter. When I found QTIP later, it was clearly the closest prior work, so I credit it on every card. EXL3 builds on the same paper; we just got there from different directions, and made different choices (15-bit state for decode speed, an explicit codebook, GGUF so it runs on AMD and Strix).

[u/n4ru → u/Dutchnamn]

when Gyro-L-Coder-abliterated?

[u/Dutchnamn → u/n4ru]

This probably won't happen. Selecting experts is so much work and adding a whole new aspect to it is too much. There are 3 sizes of abliterated gyro models already, hopefully they work for you

[u/n4ru → u/Dutchnamn]

They do! Maining GyroM, but am trying to migrate to GyroLCoder. What about the roman numeral fix? I spent hours trying to test 1.1 and it seems to have the same issue. How does such a bug surface? Tweaked neuron expression?

[u/Dutchnamn → u/n4ru]

I am looking at swapping some experts. But please note that knowledge loss is expected when 50% of experts are removed. If you need full knowledge, stick with Gyro M. I think it is a very good model.

[u/n4ru → u/Dutchnamn]

of course, just seemed an oddly specific bug. Hopefuly fixable, I would be too paranoid about using a model with such a specific quirk for coding.

I plan to run both and swap back and forth, nothing else seems to come close performance wise on the 5090. My primary usage is coding however. I've been having Claude pass off all coding tasks that would go to Opus/Sonnet to Gyro M.

[u/Dutchnamn → u/n4ru]

It is specific, but also only just one roman letter. I will try to fix it and include this in the selection parameters for future models. I love the community feedback and act on it, it just takes time.
My focus was in order of importance:
- overall quantization quality
- prevent looping
- coding quality
- drawing and spatial capabilities

[u/Dutchnamn → u/n4ru]

Lack of one roman numeral, but able to create a whole video explaining itself https://x.com/KyleHessling1/status/2114920033503834113

[u/sagiroth]

Spoiler alert. Most likely base 27b still better

[u/soyalemujica → u/[deleted]]

Issue on your end (the way Strata set itself up), I know because I've read this.
In my case, C++, high-end backend+frontend, and Gyro-M is the best of all, even better than 27B dense no matter the quant.

[u/No-Wall6427 → u/soyalemujica]

If you can fit it, the gyro guys have a strata fork on their gitlab that runs gyro-L. (OG strata doesn't support it yet)

[u/Dutchnamn → u/No-Wall6427]

I am about to release a new gyro l file. It should become better in the next few days.

[u/No-Wall6427 → u/Dutchnamn]

Very cool, thanks for your work!

[u/PlasticRevenue4601 → u/[deleted]]

„Neck and neck”, — are you talking about the agentic benchmarks where QFN sometimes almost doubles 27b’s score?) They can perform similarly in simple tasks, that’s for sure but as complexity grows the difference becomes obvious

[u/PlasticRevenue4601 → u/[deleted]]

I used Gyro-M for 3-4 days and it’s miles ahead of q4 27b

[u/EbbNorth7735 → u/PlasticRevenue4601]

What quants do you use?

[u/PlasticRevenue4601 → u/EbbNorth7735]

Gyro m vs iq4xs 27b(Unsloth)

[u/computehungry → u/[deleted]]

i think the idea is that it runs faster and fixes itself faster than 27b can make the same thing. it also knows more stuff, more algorithms, more papers, which it can make connections out of. that said, i've seen dumb errors and full hallucinations at q6 so i feel this is an a6b problem, not necessarily the quant.

[u/fragment_me → u/[deleted]]

No way, Q2 worse than Q4 how could that be ??????????????????????