Ultimate List: Best Open Models for Coding, Chat, Vision, Audio & More
Posted by techlatest_net@reddit | LocalLLaMA | View on Reddit | 32 comments
Open-source AI is evolving insanely fast, but it’s hard to know which model is actually best for each use case. So I put together a list of the best open-source models across different categories
Best Audio Generation Open Source Models
Text-to-Speech (TTS)
- Qwen3-TTS → Best overall balance (quality + speed)
- Kimi-Audio → Strong multimodal + expressive voices
- Fish Speech / Fish Audio S2 → Great for realistic voice cloning
- CosyVoice 3.0 → Very solid multilingual + streaming
- VibeVoice Realtime → Best for real-time applications
Voice Cloning
- VoxCPM2 → High-quality cloning + supports many languages
- IndexTTS2 → Clean output + good stability
- Kokoro / KokoClone → Lightweight + fast cloning
Music Generation
- ACE-Step 1.5 → Best open-source music generator right now
- Magenta Realtime → Real-time music experiments
- Uni-MoE (Audio) → Multi-purpose audio generation
Multimodal Audio (Anything → Audio)
- AudioX / Audio-Omni → Most complete multimodal audio stack
- MMAudio → Supports text, image, video → audio
- Woosh / ThinkSound → Good experimental models
Audio Enhancement
- NVIDIA A2SB → Best for restoration + inpainting
- AudioSR / NovaSR → Solid upscaling + enhancement
Speech Recognition (ASR)
- FunASR → Strong multilingual + streaming
- VibeVoice-ASR → Good real-time performance
- Cohere Transcribe (OS) → Clean + reliable
Best Image Generation Open Source Models
FLUX.1 [schnell]
Fastest open-source model balancing quality and speed for consumer GPUs.
FLUX.1 [dev]
Top benchmark leader for high-fidelity complex scenes from Black Forest Labs.
Stable Diffusion 3.5 Large
Versatile ecosystem king for fine-tuning and editing workflows.
GLM-Image
Typography specialist for bilingual infographics under Apache 2.0.
Qwen-Image-2512
Multilingual editing powerhouse for creative style transfers.
Z-Image-Turbo
Lightweight 6B real-time generator for edge and batch use.
HiDream-I1-Full
Raw photorealism expert for premium high-res outputs.
SANA-Sprint 1.6B
Ultra-efficient low-VRAM option for quick experiments.
HunyuanImage-3.0
Research-grade for advanced coherence and diversity.
Best Image to Video Geneartion Open Source Models
LTX-2.3
Leading open-source Image-to-Video model with native 4K 50fps and synchronized audio support https://huggingface.co/Lightricks/LTX-2.3.
LTX-2.3-GGUF
Quantized LTX-2.3 variant at 21B params for efficient inference on consumer hardware https://huggingface.co/unsloth/LTX-2.3-GGUF.
LTX-2.3-Workflows
ComfyUI workflows optimized for LTX-2.3 video generation pipelines https://huggingface.co/RuneXX/LTX-2.3-Workflows.
WAN2.2-14B-Rapid-AllInOne
Rapid all-in-one 14B Image-to-Video model with MoE architecture for fast local runs https://huggingface.co/Phr00t/WAN2.2-14B-Rapid-AllInOne.
VBVR-LTX2.3-diffsynth
Diffsynth integration for LTX-2.3, enabling advanced video synthesis effects https://huggingface.co/Video-Reason/VBVR-LTX2.3-diffsynth.
BFS-Best-Face-Swap-Video
Specialized LTX face-swap model for realistic video character replacement https://huggingface.co/Alissonerdx/BFS-Best-Face-Swap-Video.
Wan2.2-I2V-A14B-GGUF
14B quantized Wan2.2 for 480p/720p Image-to-Video on mid-range GPUs https://huggingface.co/QuantStack/Wan2.2-I2V-A14B-GGUF.
LTX-2
Previous LTX iteration with strong community adoption for commercial video gen https://huggingface.co/Lightricks/LTX-2.
LTX-2.3-Transition-LORA
LoRA fine-tune for smooth scene transitions in LTX-2.3 videos https://huggingface.co/valiantcat/LTX-2.3-Transition-LORA.
HY-OmniWeaving
Tencent's omni-modal Image-to-Video with multi-style weaving capabilities https://huggingface.co/tencent/HY-OmniWeaving.
Best Image to Text Generation Open Source Models
GLM-OCR
Top open-source OCR model in 2026 for speed and accuracy on complex documents https://huggingface.co/zai-org/GLM-OCR.
nemotron-ocr-v2
NVIDIA's high-precision OCR excels in scene text and multilingual recognition https://huggingface.co/nvidia/nemotron-ocr-v2.
Falcon-OCR
Efficient OCR from TII UAE for real-world text extraction in varied conditions https://huggingface.co/tiiuae/Falcon-OCR.
RationalRewards-8B-T2I
9B reward model specialized for text-to-image evaluation and captioning https://huggingface.co/TIGER-Lab/RationalRewards-8B-T2I.
RationalRewards-8B-Edit
9B variant optimized for image editing feedback and descriptive tasks https://huggingface.co/TIGER-Lab/RationalRewards-8B-Edit.
HiVG-3B-Base
4B visual grounding model for precise image-text alignment and description https://huggingface.co/xingxm/HiVG-3B-Base.
trocr-base-handwritten
Microsoft's TrOCR base for accurate handwritten text transcription https://huggingface.co/microsoft/trocr-base-handwritten.
blip-image-captioning-large
Salesforce BLIP large for detailed, high-quality image captioning https://huggingface.co/Salesforce/blip-image-captioning-large.
manga-ocr-base
Specialized OCR for Japanese manga and comic text extraction https://huggingface.co/kha-white/manga-ocr-base.
blip-image-captioning-base
Efficient BLIP base model for general-purpose image-to-text captioning https://huggingface.co/Salesforce/blip-image-captioning-base.
Best Text Generation Open Source Models
GLM-5.1
Flagship 744B MoE (40B active) from Zhipu AI leading in agentic engineering and long-horizon coding tasks https://huggingface.co/zai-org/GLM-5.1
Qwen3.5-397B-A17B
Alibaba's 397B MoE (17B active) with multimodal reasoning and 1M+ token context for versatile agents https://huggingface.co/Qwen/Qwen3.5-397B-A17B
Gemma 4
Google's hybrid attention family (2B-31B) excelling in reasoning, coding, and on-device multimodal use https://huggingface.co/google/gemma-4-31b-it
DeepSeek-V3.2
Reasoning-focused MoE with sparse attention for efficient long-context agents and GPT-5 level math https://huggingface.co/deepseek-ai/DeepSeek-V3.2
Kimi-K2.5
Moonshot's 1T MoE (32B active) multimodal model for visual coding and agent swarms up to 100 sub-agents https://huggingface.co/moonshotai/Kimi-K2.5
MiniMax-M2.7
Self-improving agentic LLM topping SWE-Pro benchmarks for real-world software engineering workflows https://huggingface.co/MiniMaxAI/MiniMax-M2.7
MiMo-V2-Flash
Xiaomi's efficient 309B MoE (15B active) with 150 t/s throughput for high-volume coding agents https://huggingface.co/XiaomiMiMo/MiMo-V2-Flash
R_Duncan@reddit
Omnivoice beats all the TTS models listed by expressivenes, foreign-languages inflection, size and speed.
ecompanda@reddit
the problem with any 'best models' list right now is the half life is about 3 weeks. Qwen 3.6 Plus dropped this month and already reshuffled the coding leaderboard, same pattern happened when Gemma 4 came out. someone in the comments already flagging PocketTTS and Parakeet V3 which aren't here. hard to keep these current without a weekly update cadence.
Free-Combination-773@reddit
Wonderful AI slop
HeavyConfection9236@reddit
Damn. Is there a better, human created list somewhere that stays up to date? Or is it just browsing huggingface for trending models?
kartikgsniderj@reddit
Artificial Analysis, and Huggingface Spaces
Cold_Tree190@reddit
Yup, and it even loses its formatting partway through the post lol. That’s when I realized I was looking at slop and just scrolled
ToInfinityAndAbove@reddit
I'm getting tired of seeing these comments everywhere now. Focus on the content itself, who cares if it's written by AI?
GludiusMaximus@reddit
> Open-source AI is evolving insanely fast, but it’s hard to know which model is actually best for each use case.
I think this is a human-written post, AI actually knows the difference between "but" and "and"
ThisGonBHard@reddit
It is slop.
It has Flux 1 models but no Flux 2.
Also no Anima 2B.
HeavyConfection9236@reddit
Typically the reason AI written posts are regarded as "slop" is *because* the content that AI writes tends to be sensationalist, factually inconsistent, outdated, or completely hallucinated.
jokab@reddit
I get your point. but somebody else bothered to publish this slop and so happens I, and seemingly many others, am curious to know.
Free-Combination-773@reddit
This post is fucking slop, and it's written in typical chaygpt manner, therefore - AI slop. This term has two words in it
FreonMuskOfficial@reddit
Combo pizza roll guy does.
No-Refrigerator-1672@reddit
Yeah, the list is not even up to date, some of the mentioned models were updated to a better version.
Confusion_Senior@reddit
omnivoice
rkoy1234@reddit
no streaming tho, which is my only gripe
LadyQuacklin@reddit
omnivoice is by far the best.
Small, fast, good quality, one shot cloning, nonverbal tags, voice design, streaming. Over 600 Languages
So much in such a small model
alext77777@reddit
absolutely right, it's by far the best TTS and cloning model, how can it not be in the list ?!?
GludiusMaximus@reddit
I hear a lot about one-shot zero-shot voice cloning, but on the off-chance you or someone else knows: is the Chinese very mainland inflected? I find this with most open source models, they have a hard time losing the mainland Chinese accent (I have tried other models, working with cloning a Taiwanese voice)
nortca@reddit
Are any of the new ASR models good for generating for long form like movie subtitles?
Whisper still my go-to after all this time because implementations support video input and batched chunking.
_raydeStar@reddit
There needs to be a new field here -- TTS fast enough to hold a conversation (latency under a second or half second or something like that)
It's two different workhorses -- audiobooks and AI videos versus real time chat with an AI
SomeRandomGuuuuuuy@reddit
Looks like a Slope but maybe I will use the views of this post anybody figured out local video editing to automate changing scene creating picture for learning or something like this Qwen-edit seems best ?
GludiusMaximus@reddit
> Open-source AI is evolving insanely fast, but it’s hard to know which model is actually best for each use case.
I think this is a human-written post, AI actually knows the difference between "but" and "and"
Haeppchen2010@reddit
Hmm throwing some dice against a wall would have saved some watt hours, and had produced a similarly trustworthy, fact-based, useable amount of information. /s
SatoshiNotMe@reddit
This misses the STT/TTS models I regularly use:
PocketTTS from KyutAI
Parakeet V3 for STT
_Denil_@reddit
Add to voice cloning Qwen3-TTS (It has a voice cloning function) Add to music generation Ace Step 1.5 XL Add to image generation Ernie image
FluentFreddy@reddit
Great list, several I’m looking forward to trying
Sea_Cardiologist2050@reddit
thanks, really helpful!
snek_kogae@reddit
Nice, as someone who works in the ocr space, definitely vouch for chandra and lighton ocr too (v2 for both)
agentXchain_dev@reddit
Useful list, but for LocalLLaMA the missing piece is deployment constraints. A model that wins on quality can still lose hard if it needs 24 GB VRAM, has a restrictive license, or falls apart on llama.cpp or vLLM, so a small table with VRAM, tokens per second, and license would make this way more actionable.
Visual_Internal_6312@reddit
Also platform, for instance fish speech doesn't work on Mac afaik
Long_comment_san@reddit
Nice