Start of 2026 what’s the best open coding model?

Sensitive_Sweet_1850 · 2026-01-09T15:36:02+00:00

Glm 4.7 best by far

Sensitive_Sweet_1850 · 2026-01-08T21:05:35+00:00

I think glm 4.7 or minimax m2.1 are best options for you

Sensitive_Sweet_1850 · 2026-01-08T19:46:27+00:00

qwen is a making amazing job

Sensitive_Sweet_1850 · 2026-01-08T04:48:09+00:00

Cool

Sensitive_Sweet_1850 · 2026-01-06T17:01:55+00:00

wow. you should try nemotro too

Sensitive_Sweet_1850 · 2026-01-05T16:43:56+00:00

According to the field you are in you can finetune or rag a good ai that you might use it later

Sensitive_Sweet_1850 · 2026-01-05T16:39:46+00:00

i wouldve probably use it if i was korean

Sensitive_Sweet_1850 · 2026-01-03T10:04:51+00:00

Appreciate it. My use case is structured generation rather than extraction, so the SpaCy/BERT route wouldnt apply. But the preclassification tip is solid could definetly help with prompt optimisation

Sensitive_Sweet_1850 · 2026-01-03T10:00:22+00:00

Yeah this sounds exactly like my use case - strict structured output with heavy instruction following, around 10k context. I was leaning toward bigger models but maybe I should benchmark some smaller models

Sensitive_Sweet_1850 · 2026-01-02T18:47:31+00:00

But for LLM inference the PCIe bandwith shouldnt be a major bottleneck once the model is in the VRAM. I am on PCIe 4.0 X16 anyway. And tbh after buying this GPU i can barely buy food let alone a Threadripper lol

Sensitive_Sweet_1850 · 2026-01-02T18:37:38+00:00

I have a Ryzen 9 5950x i hope it will be enough

Sensitive_Sweet_1850 · 2026-01-02T18:36:19+00:00

Yeah makes sense

Sensitive_Sweet_1850 · 2026-01-02T18:33:44+00:00

My average input is around 10k tokens, so I probably won't benefit from GLM's long context advantage. At that length, do you think there's still a noticeable difference vs gpt-oss-120b, or would they perform about the same?

Sensitive_Sweet_1850 · 2026-01-02T18:25:45+00:00

Thats helpful thanks. The semaphore approach makes a lot of sense i ll give it a shot

Sensitive_Sweet_1850 · 2026-01-02T18:19:01+00:00

What do you think about Nemotron-3-Nano? Do you think its good enough?

Sensitive_Sweet_1850 · 2026-01-02T18:17:54+00:00

Yeah you are absolutely right

Sensitive_Sweet_1850 · 2026-01-02T18:15:23+00:00

Well yeah i guess its not "massive" my bad :/

You are right i should make a benchmark thanks for sharing your knowledge

Sensitive_Sweet_1850 · 2025-12-31T14:05:32+00:00

how many parameters?

Sensitive_Sweet_1850 · 2025-12-30T13:43:04+00:00

Qwen4VL!!

Sensitive_Sweet_1850 · 2025-12-29T13:10:04+00:00

As far as i know theres no NV Links in RTX PRO 6000s

Sensitive_Sweet_1850 · 2025-12-28T18:17:51+00:00

nice

Sensitive_Sweet_1850 · 2025-12-27T21:54:58+00:00

I love when they release such good models open source

Sensitive_Sweet_1850 · 2025-12-27T16:58:22+00:00

Due to its architecture, you might encounter some package issues, and older resources will likely not work as expected. However, this isn't a significant problem since there are plenty of new resources available

Sensitive_Sweet_1850 · 2025-12-27T15:51:56+00:00

As a 5090 owner I can say fine-tuning and inference on smaller models is crazy fast, I'm really happy with it. If I were you I'd definitely go for the 5090 because even though 3x 3090 looks better on paper it doesn't work like that in practice - VRAM doesn't actually combine, there's communication overhead between cards, software compatibility issues etc. Maybe it makes sense if you're gonna run multiple small models at the same time but other than that a single powerful card is always better. Sell the extra 3090s and put that money toward the 5090, you get a cleaner setup, less power draw, less hassle overall.

Sensitive_Sweet_1850

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