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GROUNDED IN REAL HUMAN CONVERSATIONSYOUR BENCH
Qwen3 14B
◆ OPEN
by Alibaba
OPEN WEIGHTSLOCALAPIPAIDREASONINGCLOSED
RANKED #178 OF 228 ASSISTANTS · OVERALL #277 OF 6,618 · VIBE SCORE 5.5 · 97 VOICES
Qwen3-14B is a dense 14.8B parameter causal language model from the Qwen3 series, designed for both complex reasoning and efficient dialogue. It supports seamless switching between a "thinking" mode for...
HAPPY7.7
10 mentions
SAD7.3
7 mentions
VIBE TRAJECTORY
26 weeks · 115 voices
HOLDING UP
Recent vibe is steady. No clear fade in the crowd.
HOW TO USE IT
Open weights. You can use a hosted service, or download it and run it yourself, free.
RUN IT ON YOUR OWN MACHINE
Open weights: download Qwen3 14B once and it's yours. No subscription, no rate limits, works offline.
14B parameters, a Q4_K_M quantized file is about 9 GB while unquantized FP16 is about 29 GB
- BARE MINIMUM
NVIDIA GeForce RTX 3060 12GB
12 GB VRAM
~$280 USEDQ4_K_M quant, full GPU offload, ~25 tok/s, 8k context
- SWEET SPOT
NVIDIA GeForce RTX 4070 Super 12GB
12 GB VRAM
~$590 NEWQ5_K_M quant, fast daily inference, ~40 tok/s, 16k context
- FULL POWER
NVIDIA GeForce RTX 3090 24GB
24 GB VRAM
~$750 USEDQ8_0 or FP16 unquantized, full precision, ~50 tok/s, 32k+ context
LEARN HOW TO SET IT UP
WILL MY BOX RUN QWEN3 14B?
The three cards above are researched picks. Search the machine you actually have — we only say yes if it should reply at a usable speed, not just load the weights and crawl.
HARDWARE PICKS & PRICES ARE RESEARCHED FROM THE LIVE WEB AND REFRESHED AUTOMATICALLY. TREAT THEM AS BALLPARK, NOT GOSPEL.
WHAT CAN YOU ACTUALLY DO WITH IT?
Everyday jobs on each of those rigs: how long Qwen3 14B takes, and how good the crowd says it is at that kind of work.
| THE JOB | BARE MINIMUMNVIDIA GeForce RTX 3060 12GB | SWEET SPOTNVIDIA GeForce RTX 4070 Super 12GB | FULL POWERNVIDIA GeForce RTX 3090 24GB |
|---|---|---|---|
| Write an emaila paragraph or two, drafted from a one-line brief | ~20 S★★★★★ | ~13 S★★★★★ | ~10 S★★★★★ |
| Summarize a documenta long report boiled down to the points that matter | ~60 S★★★★★ | ~38 S★★★★★ | ~30 S★★★★★ |
| Build a websitea small landing page, markup and styles together | ~5.3 MIN★★★★★ | ~3.3 MIN★★★★★ | ~2.7 MIN★★★★★ |
| Build a backendan API with routes, storage and tests | ~17 MIN★★★★★ | ~10 MIN★★★★★ | ~8.3 MIN★★★★★ |
| Build a gamea playable browser game in one file | ~10 MIN★★★★★ | ~6.3 MIN★★★★★ | ~5 MIN★★★★★ |
STARS ARE THE COMMUNITY SCORE FOR THAT KIND OF WORK, DOCKED FOR HOW SQUASHED THE WEIGHTS GET AT EACH TIER. TIMES ARE COMPUTED FROM RESEARCHED SPEEDS. BALLPARK, NOT GOSPEL.
WHAT THE INTERNET SAYS
Not enough discussion about Qwen3 14B yet to call it. We found 97 posts but people did not say much either way.
78 POSTS · 19 COMMENTS · STACK OVERFLOW · REDDIT · X · GITHUB · LEMMY · DEV FORUMS · BLUESKY · OTHER FORUMS
PEOPLE LOVE
- No fan mail yet. The crowd is still warming up.
PEOPLE COMPLAIN ABOUT
- No complaints yet. The internet is still looking for one. Suspicious.
LOOKING FOR AN ALTERNATIVE?
Other models the crowd has fully reviewed, starting with text models like this one.
GLM 5.3
DeepSeek V4 Flash> SOURCES (12)
- REDDIT · 2025-05-09 · 68 UPVOTESBuilt a simple way to one-click install and connect MCP servers to Ollama (Open source local LLM client)
Built a simple way to one-click install and connect MCP servers to Ollama (Open source local LLM client)
- REDDIT · 2026-03-12 · 46 UPVOTESSqueezing a 14B model + speculative decoding + best-of-k candidate generation into 16GB VRAM- here's what it took
Squeezing a 14B model + speculative decoding + best-of-k candidate generation into 16GB VRAM- here's what it took
- LEMMY · 2026-06-25 · 33 UPVOTESModels for 16 GB vram?
Models for 16 GB vram?
- REDDIT · 2025-08-18 · 32 UPVOTESWhy does Qwen3 (8B & 14B) have a smaller context window than Qwen3 (4B)?
Why does Qwen3 (8B & 14B) have a smaller context window than Qwen3 (4B)?
- REDDIT · 2026-08-19 · 29 UPVOTES[Open PR] llama : add --n-cpu-ffn option by John-194 · Pull Request #26622 · ggml-org/llama.cpp
[Open PR] llama : add --n-cpu-ffn option by John-194 · Pull Request #26622 · ggml-org/llama.cpp
- REDDIT · 2026-04-10 · 20 UPVOTESHow a $500 GPU beat Claude Sonnet on a coding benchmark (and why the "secret" isn't the model)
How a $500 GPU beat Claude Sonnet on a coding benchmark (and why the "secret" isn't the model)
- LEMMY · 2026-02-24 · 19 UPVOTESCar Wash Test on 53 leading AI models: "I want to wash my car. The car wash is 50 meters away. Should I walk or drive?"
Car Wash Test on 53 leading AI models: "I want to wash my car. The car wash is 50 meters away. Should I walk or drive?"
- REDDIT · 2025-11-04 · 17 UPVOTES⚡️ I scaled Coding-Agent RL to 32x H100s. Achieving 160% improvement on Stanford's TerminalBench. All open source!
⚡️ I scaled Coding-Agent RL to 32x H100s. Achieving 160% improvement on Stanford's TerminalBench. All open source!
- LEMMY · 2025-06-10 · 14 UPVOTESCurrent best local models for tool use?
Current best local models for tool use?
- REDDIT · 2026-08-01 · 12 UPVOTESLocal Ollama models
Local Ollama models
- REDDIT · 2026-06-09 · 10 UPVOTESWhat is your current local LLM setup?
What is your current local LLM setup?
- REDDIT · 2025-07-06 · 9 UPVOTESOllama use A LOT of memory even after offloading model to GPU
Ollama use A LOT of memory even after offloading model to GPU