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Qwen2.5 1.5B Instruct
◆ OPEN
by Alibaba
OPEN WEIGHTSLOCALCHINA-MADEAPIPAIDEUROPE-MADE
RANKED #231 OF 271 ASSISTANTS · OVERALL #366 OF 6,567 · VIBE SCORE 5.3 · 28 VOICES
Qwen2.5-1.5B-Instruct-unsloth-bnb-4bit on Hugging Face (text generation). 119,124 downloads. Open weights for local or hosted use.
HAPPY7.4
3 mentions
SAD7.6
3 mentions
VIBE TRAJECTORY
26 weeks · 40 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 Qwen2.5 1.5B Instruct once and it's yours. No subscription, no rate limits, works offline.
1.54B parameters, a Q4_K_M file is about 986 MB (full FP16 is around 3.1 GB)
- BARE MINIMUM
Raspberry Pi 5 (8GB) or budget laptop CPU
8 GB RAM
~$80Q4_K_M on CPU, ~12 tok/s, 8k context
- SWEET SPOT
NVIDIA GeForce GTX 1650 4GB
4 GB VRAM
~$85 USEDQ8_0 or FP16 fully offloaded to GPU, ~60 tok/s, 32k context
- FULL POWER
NVIDIA GeForce RTX 3060 12GB
12 GB VRAM
~$260 USEDUnquantized FP16 with full 128k context window offloaded to VRAM, ~140 tok/s
LEARN HOW TO SET IT UP
WILL MY BOX RUN QWEN2.5 1.5B INSTRUCT?
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 Qwen2.5 1.5B Instruct takes, and how good the crowd says it is at that kind of work.
| THE JOB | BARE MINIMUMRaspberry Pi 5 (8GB) or budget laptop CPU | SWEET SPOTNVIDIA GeForce GTX 1650 4GB | FULL POWERNVIDIA GeForce RTX 3060 12GB |
|---|---|---|---|
| Write an emaila paragraph or two, drafted from a one-line brief | ~42 S★★★★★ | ~8 S★★★★★ | ~4 S★★★★★ |
| Summarize a documenta long report boiled down to the points that matter | ~2.1 MIN★★★★★ | ~25 S★★★★★ | ~11 S★★★★★ |
| Build a websitea small landing page, markup and styles together | ~11 MIN★★★★★ | ~2.2 MIN★★★★★ | ~57 S★★★★★ |
| Build a backendan API with routes, storage and tests | ~35 MIN★★★★★ | ~6.9 MIN★★★★★ | ~3 MIN★★★★★ |
| Build a gamea playable browser game in one file | ~21 MIN★★★★★ | ~4.2 MIN★★★★★ | ~1.8 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 Qwen2.5 1.5B Instruct yet to call it. We found 28 posts but people did not say much either way.
25 POSTS · 3 COMMENTS · REDDIT · GITHUB · DEV 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.
DeepSeek V4 Flash> SOURCES (12)
- REDDIT · 2026-03-03 · 21 UPVOTES[P] I trained Qwen2.5-1.5b with RLVR (GRPO) vs SFT and compared benchmark performance
[P] I trained Qwen2.5-1.5b with RLVR (GRPO) vs SFT and compared benchmark performance
- REDDIT · 2025-07-07 · 17 UPVOTESOrangePi Zero 3 runs Ollama
OrangePi Zero 3 runs Ollama
- REDDIT · 2025-09-13 · 4 UPVOTESSo many models...confused how to pick the right one. Need one to help fix English grammar and text.
So many models...confused how to pick the right one. Need one to help fix English grammar and text.
- REDDIT · 2026-07-10 · 2 UPVOTESSuper-Lite Cyber Coder (Qwen2.5 1.5B) - 4-bit GGUF for low-spec local coding & security tasks
Super-Lite Cyber Coder (Qwen2.5 1.5B) - 4-bit GGUF for low-spec local coding & security tasks
- REDDIT · 2024-10-19 · 2 UPVOTESautotrain problem
autotrain problem
- GITHUB · 2026-08-31 · 1 UPVOTESfix(ollama): reconstruct streaming tool calls, indices, finish_reason and error chunks
fix(ollama): reconstruct streaming tool calls, indices, finish_reason and error chunks
- DEV FORUMS · 2026-09-04 · 1 UPVOTESLooking for Windows users with 2–8 GB GPUs to test a low-VRAM local LLM runtime
Looking for Windows users with 2–8 GB GPUs to test a low-VRAM local LLM runtime
- GITHUB · 2026-08-28 · 1 UPVOTES[v0.23.0][Bugfix] Validate stop_token_ids against vocab size (backport of vllm#54196)
[v0.23.0][Bugfix] Validate stop_token_ids against vocab size (backport of vllm#54196)
- DEV FORUMS · 2026-02-04 · 0 UPVOTESVllm推理问题，推理结果完全不对
Vllm推理问题，推理结果完全不对
- GITHUB · 2026-08-19 · 0 UPVOTESLocal LLM broad A/B: Llama 3.2 1B vs qwen2.5:1.5b
Local LLM broad A/B: Llama 3.2 1B vs qwen2.5:1.5b
- GITHUB · 2026-08-22 · 0 UPVOTESAccept Llama 3.2's terms, or switch to a permissively licensed model?
Accept Llama 3.2's terms, or switch to a permissively licensed model?
- DEV FORUMS · 2026-08-28 · 0 UPVOTES“OpenAI-compatible" is a spectrum, not a boolean 12 things that silently break when you swap providers
“OpenAI-compatible" is a spectrum, not a boolean 12 things that silently break when you swap providers