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Qwen Model Version Comparisons

BACKGROUND
21 SIGNALSFIRST DETECTED 11 May 2026UPDATED 19 May 2026
The NewsHive View

The trouble started on May 11th, when a LocalLLaMA user posted a question that sounds simple but cuts deep: why does Qwen3.6-35B-A3B feel noticeably less capable than the version before it? Not a benchmark anomaly. Not a theoretical regression. A practitioner running models locally noticed that a newer version number was producing worse outputs, and they wanted to know why. That post scored a modest 6.4, suggesting the observation resonated with enough people to bubble up without going viral. Then, eight days later, a second signal arrived — a direct performance comparison between Qwen3-Coder-Next and Qwen3.6-27B-MTP, both run on Strix Halo hardware in quantized form. The framing here shifted from complaint to investigation, with someone actually putting two versions side by side in a controlled-enough environment to draw comparisons. Together, these two posts sketch the outline of a community quietly losing confidence in the versioning logic behind Qwen's rapid release cadence.

If confirmed, here is what this means. Alibaba's Qwen team has been releasing model variants at a pace that is genuinely impressive — and apparently, at a pace that is outrunning quality control on at least some capability dimensions. For developers building local applications on top of Qwen models, version number is supposed to be a reliable proxy for capability. When it isn't, every upgrade decision becomes a gamble. The second-order effect is trust erosion: the open-weights community is unusually attentive to exactly this kind of regression, and word travels fast. If Qwen 3.6 is genuinely underperforming Qwen 3.5 on practical tasks despite the higher version number, that creates a real documentation and communication problem for Alibaba — particularly as it competes for developer mindshare against Mistral, Meta, and others who are also pushing frequent updates. The MTP (multi-token prediction) architecture variant adds another layer of complexity, since comparing MTP models to standard ones isn't apples-to-apples, and many users may not realize that.

Watch for official Qwen release notes or community moderator posts that address the versioning confusion directly — and pay particular attention to whether benchmark scores on coding tasks specifically show a gap between the 3.5 and 3.6 generations.

How the story developed
19 Oct
incoai/Qwen3.8-Flash-Next-DFlash2
OPINION · WHAT · LocalLLaMA
2.9
15 Oct
2.5
5 Oct
GLM 5.3 Flash v Tencent Hy3
OPINION · WHAT · LocalLLaMA
1.8
1 Oct
How to know about optimized engines
OPINION · HOW · LocalLLaMA
1.0
26 Sept
26 Sept
23 Sept
Qwen FN vs 27B --- Think I'm saturated.
OPINION · WHAT · LocalLLaMA
14 Jun
Qwen3.6 is confidently wrong about WASM
OPINION · WHAT · LocalLLaMA
Other feeds and industry voices
30 Mar
Qwen3.5 Omni - Qwen’s latest generation of fully omnimodal LLM

<table> <tr><td> <a href="https://www.reddit.com/r/singularity/comments/1s7rcwr/qwen35_omni_qwens_latest_generation_of_fully/"> <img alt="Qwen3.5 Omni - Qwen’s latest generation

OPINION · WHAT · singularityOPEN STORY
26 Mar
1 million tokens per second from a single cluster, what that actually means

<!-- SC_OFF --><div class="md"><p>Got Qwen 3.5 27B to 1,103,941 tok/s on 12 nodes with 96 B200 GPUs.</p> <p>At that rate you process 50,000 insurance policy documents in hours

OPINION · WHAT · singularityOPEN STORY
24 Mar
Distilled qwen 3.5 27b is surprisingly good at driving Cursor.

<!-- SC_OFF --><div class="md"><p>I'm using this <a href="https://huggingface.co/Jackrong/Qwen3.5-27B-Claude-4.6-Opus-Reasoning-Distilled-v2-GGUF">opus 4.6 distilled version of

OPINION · HOW · LocalLLaMAOPEN STORY
8 Apr
Napkin math: KV cache for Llama 3.1 at 128K context is ~64GB per decode request, and that's after GQA

<!-- SC_OFF --><div class="md"><p>Every output token the model generates requires reading the entire KV cache from High Bandwidth Memory.</p> <p>Here's what that actually looks

OPINION · WHAT · LocalLLaMAOPEN STORY
6 May
2.5x faster inference with Qwen 3.6 27B using MTP - Finally a viable option for local agentic coding - 262k context on 48GB - Fixed chat template - Drop-in OpenAI and Anthropic API endpoints

<!-- SC_OFF --><div class="md"><blockquote> <p><strong>WARNING: wait before download from HF: I just realised my upload of the new versions with the additional fix in the chat

OPINION · HOW · LocalLLaMAOPEN STORY
25 Mar
Qwen3.5-397B-A17B reaches 20 t/s TG and 700t/s PP with a 5090

<!-- SC_OFF --><div class="md"><p>I could not find good data points on what speed one could get with a single 5090 and enough DDR4 RAM. </p> <p>My system: AMD EPYC 7532 32core

OPINION · WHAT · LocalLLaMAOPEN STORY
21 Apr
Where we are. In a year, everything has changed. Kimi - Minimax - Qwen - Gemma - GLM

<table> <tr><td> <a href="https://www.reddit.com/r/LocalLLaMA/comments/1srhtvg/where_we_are_in_a_year_everything_has_changed/"> <img alt="Where we are. In a year, everything has

OPINION · WHERE · LocalLLaMAOPEN STORY
16 Apr
Qwen3.6-35B-A3B released!

<table> <tr><td> <a href="https://www.reddit.com/r/LocalLLaMA/comments/1sn3izh/qwen3635ba3b_released/"> <img alt="Qwen3.6-35B-A3B released!"

OPINION · WHAT · LocalLLaMAOPEN STORY
Sources
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