LOADING DATASHEET
LOADING DATASHEET
by Mistral
RANKED #254 OF 271 ASSISTANTS · OVERALL #396 OF 6,567 · VIBE SCORE 5.0 · 29 VOICES
Mistral-7B-Instruct-v0.3 model is a fine-tuned version of the Mistral 7B base model, optimized for instruction-following tasks. Released in 2023, it is intended for demonstration purposes and does not include built-in guardrails or moderati
0 mentions
4 mentions
26 weeks · 12 voices
TOO QUIET
Not enough weekly voices to call a trend yet.
Open weights. You can use a hosted service, or download it and run it yourself, free.
Open weights: download 7B instruct v0.3 once and it's yours. No subscription, no rate limits, works offline.
7.25B parameters, a Q4_K_M GGUF is about 4.4 GB, full FP16 is around 14.5 GB
NVIDIA GeForce GTX 1660 Super (6 GB)
6 GB VRAM + 16 GB SYSTEM RAM
~$110 USEDQ4_K_M, ~22 tok/s, 8k context offloaded
NVIDIA GeForce RTX 3060 (12 GB)
12 GB VRAM
~$260 USEDQ8_0 or Q5_K_M, ~65 tok/s, full 32k context on GPU
NVIDIA GeForce RTX 4070 Ti Super (16 GB)
16 GB VRAM
~$780 NEWFP16 or Q8_0, ~110 tok/s, full 32k context at maximum speed
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.
Everyday jobs on each of those rigs: how long 7B instruct v0.3 takes, and how good the crowd says it is at that kind of work.
| THE JOB | BARE MINIMUMNVIDIA GeForce GTX 1660 Super (6 GB) | SWEET SPOTNVIDIA GeForce RTX 3060 (12 GB) | FULL POWERNVIDIA GeForce RTX 4070 Ti Super (16 GB) |
|---|---|---|---|
| Write an emaila paragraph or two, drafted from a one-line brief | ~23 S★★★★★ | ~8 S★★★★★ | ~5 S★★★★★ |
| Summarize a documenta long report boiled down to the points that matter | ~68 S★★★★★ | ~23 S★★★★★ | ~14 S★★★★★ |
| Build a websitea small landing page, markup and styles together | ~6.1 MIN★★★★★ | ~2.1 MIN★★★★★ | ~73 S★★★★★ |
| Build a backendan API with routes, storage and tests | ~19 MIN★★★★★ | ~6.4 MIN★★★★★ | ~3.8 MIN★★★★★ |
| Build a gamea playable browser game in one file | ~11 MIN★★★★★ | ~3.8 MIN★★★★★ | ~2.3 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.
Not enough discussion about 7B instruct v0.3 yet to call it. We found 29 posts but people did not say much either way.
22 POSTS · 7 COMMENTS · DEV FORUMS · LEMMY · REDDIT · STACK OVERFLOW · GITHUB
Other models the crowd has fully reviewed, starting with text models like this one.
Summary: The big AI events of the great 2024
Simple RAG + Web Search + PDF Chat
[P] New collection of Llama, Mistral, Phi, Qwen, and Gemma models for function/tool calling
AI boyfriend users radicalise against OpenAI — and self-host their chatbot companions
D2 sidecars for Mistral-7B-Instruct-v0.3: near-Q8 128K retrieval at lower KV memory
This week in AI - all the Major AI developments in a nutshell
[Help] How to fine-tune Mistral-7B-Instruct-v0.3 to become a DevOps & Cloud tutor AI?
This week in AI - all the Major AI developments in a nutshell
Simple RAG + Web Search + PDF Chat
Let's test different models on counting e in Deepseek.
Comment in r/singularity
Presenting TIS (Token Importance Scoring) - A new way to compress KV cache