GLM-5.2-MTP-MLX
inferencerlabs基础档案已收录，详细介绍后续补充。可先查看厂商、分类与来源。
Basic profile indexed · More details to follow
Input Text · Image→ Output Text
Price not verifiedCheck multimodal and channel pricing separately
View details ↗DISCOVER & COMPARE
Explore AI models 84999
GLM-5.3-Flash-MLX-Q9
inferencerlabs基础档案已收录，详细介绍后续补充。可先查看厂商、分类与来源。
Basic profile indexed · More details to follow
Input Text · Image→ Output Text
Price not verifiedCheck multimodal and channel pricing separately
View details ↗Kolibri-MLX-Q9
inferencerlabs基础档案已收录，详细介绍后续补充。可先查看厂商、分类与来源。
Basic profile indexed · More details to follow
Input Text→ Output Text
Price not verifiedCheck multimodal and channel pricing separately
View details ↗MiMo-V2.6-Flash-RL-MLX-Q9
inferencerlabs基础档案已收录，详细介绍后续补充。可先查看厂商、分类与来源。
Basic profile indexed · More details to follow
Input Text · Image→ Output Text
Price not verifiedCheck multimodal and channel pricing separately
View details ↗MiMo-V2.6-Pro-RL-MLX-Q9
inferencerlabs基础档案已收录，详细介绍后续补充。可先查看厂商、分类与来源。
Basic profile indexed · More details to follow
Input Text · Image→ Output Text
Price not verifiedCheck multimodal and channel pricing separately
View details ↗Muse-Spark-Open-816B-A42B-MLX-Q4i
inferencerlabs基础档案已收录，详细介绍后续补充。可先查看厂商、分类与来源。
Basic profile indexed · More details to follow
Input Text · Image→ Output Text
Price not verifiedCheck multimodal and channel pricing separately
View details ↗NVIDIA-Nemotron-3-Super-120B-A12B-MLX-Q4
inferencerlabs基础档案已收录，详细介绍后续补充。可先查看厂商、分类与来源。
Basic profile indexed · More details to follow
Input Text→ Output Text
Price not verifiedCheck multimodal and channel pricing separately
View details ↗Qwen3.8-Flash-Next-MLX-Q4i
inferencerlabs基础档案已收录，详细介绍后续补充。可先查看厂商、分类与来源。
Basic profile indexed · More details to follow
Input Text · Image→ Output Text
Price not verifiedCheck multimodal and channel pricing separately
View details ↗Qwen3.8-Flash-Next-MLX-Q6s
inferencerlabs基础档案已收录，详细介绍后续补充。可先查看厂商、分类与来源。
Basic profile indexed · More details to follow
Input Text · Image→ Output Text
Price not verifiedCheck multimodal and channel pricing separately
View details ↗Qwen3.8-Flash-Next-MLX-Q9
inferencerlabs基础档案已收录，详细介绍后续补充。可先查看厂商、分类与来源。
Basic profile indexed · More details to follow
Input Text · Image→ Output Text
Price not verifiedCheck multimodal and channel pricing separately
View details ↗Qwen3.8-Flash-Next-MLX-Q9s
inferencerlabs基础档案已收录，详细介绍后续补充。可先查看厂商、分类与来源。
Basic profile indexed · More details to follow
Input Text · Image→ Output Text
Price not verifiedCheck multimodal and channel pricing separately
View details ↗Qwen3.8-Flash-Next-MLX-Q9se
inferencerlabs基础档案已收录，详细介绍后续补充。可先查看厂商、分类与来源。
Basic profile indexed · More details to follow
Input Text · Image→ Output Text
Price not verifiedCheck multimodal and channel pricing separately
View details ↗Qwen3-Coder-Next-MLX-Q9
inferencerlabs基础档案已收录，详细介绍后续补充。可先查看厂商、分类与来源。
Basic profile indexed · More details to follow
Input Text→ Output Text
Price not verifiedCheck multimodal and channel pricing separately
View details ↗Llama-3.3-70B-Instruct-FP8-Dynamic
Infermatic基础档案已收录，详细介绍后续补充。可先查看厂商、分类与来源。
Basic profile indexed · More details to follow
Input Text→ Output Text
Price not verifiedCheck multimodal and channel pricing separately
View details ↗stella-base-en-v2
infgrad基础档案已收录，详细介绍后续补充。可先查看厂商、分类与来源。
Basic profile indexed · More details to follow
Input Text→ Output Embedding
Price not verifiedCheck multimodal and channel pricing separately
View details ↗stella-base-zh-v3-1792d
infgrad基础档案已收录，详细介绍后续补充。可先查看厂商、分类与来源。
Input Text→ Output Embedding
Price not verifiedCheck multimodal and channel pricing separately
View details ↗stella-large-zh-v2
infgrad1. 开源数据(wudao_base_200GB[1]、m3e[2]和simclue[3])，着重挑选了长度大于512的文本 2. 在通用语料库上使用LLM构造一批(question, paragraph)和(sentence, paragraph)数据 1. 对比学习损失函数 2. 带有难负例的对比学习损失函数(分别基于bm25和vector构造了难负例) 3. EWC(Elastic Weights Consolidation)[4] 4. cosent loss[5] 5. 每一种类型的数据一个迭代器，分别计算loss进行更新 stella-v2在stella模型的基础上，使用了更多的训练数据，同时知识蒸馏等方法去除了前置的instruction( 比如piccolo的`查询:`, `结果:`, e5的`query:`和`passage:`)。
Translation queued · Showing source text
Input Text→ Output Embedding
Price not verifiedCheck multimodal and channel pricing separately
View details ↗shieldgemma-2-4b-it-GGUF
infil00p基础档案已收录，详细介绍后续补充。可先查看厂商、分类与来源。
Basic profile indexed · More details to follow
Input Image→ Output Not verified
Price not verifiedCheck multimodal and channel pricing separately
View details ↗Krea2-CyberRealistic-v4-BF16
Infini-Srr基础档案已收录，详细介绍后续补充。可先查看厂商、分类与来源。
Basic profile indexed · More details to follow
Input Text→ Output Image
Price not verifiedCheck multimodal and channel pricing separately
View details ↗gemma-4-31B-it-uncensored
InfinimindCreations基础档案已收录，详细介绍后续补充。可先查看厂商、分类与来源。
Basic profile indexed · More details to follow
Input Text→ Output Text
Price not verifiedCheck multimodal and channel pricing separately
View details ↗gemma-4-E4B-it-uncensored
InfinimindCreations基础档案已收录，详细介绍后续补充。可先查看厂商、分类与来源。
Input Text→ Output Text
Price not verifiedCheck multimodal and channel pricing separately
View details ↗gemma-4-E4B-it-uncensored-vision
InfinimindCreations基础档案已收录，详细介绍后续补充。可先查看厂商、分类与来源。
Input Text · Image→ Output Text
Price not verifiedCheck multimodal and channel pricing separately
View details ↗K2-Horizon-MoVA-36B-A4B-uncensored-GGUF
InfinimindCreations基础档案已收录，详细介绍后续补充。可先查看厂商、分类与来源。
Basic profile indexed · More details to follow
Input Text→ Output Text
Price not verifiedCheck multimodal and channel pricing separately
View details ↗Spark-X2.5-4B-uncensored-GGUF
InfinimindCreationsQuantized GGUF builds of InfinimindCreations/Spark-X2.5-4B-uncensored, an abliterated Spark-X2.5-4B with 0 refusals across 400 harmful prompts and no measurable capability loss (perplexity change -0.06 %). Evaluation details and method are on the source model card. Spark-X2.5 support lives in a fork, XHToken/llama.cpp. Upstream llama.cpp has no `Spark2_5` converter and Ollama 0.33.3 rejects the file with `failed to validate GGUF with llama-quantize without compatibility patches`. Measured, not assumed: we hit exactly that error. Spark writes into a reasoning block by default. Through an OpenAI-compatible endpoint the visible `content` is then empty while the actual answer sits in `reasoning_content`. Pass `enable_thinking: false`, or run Ollama with `--think=false`.
Input Text→ Output Text
Price not verifiedCheck multimodal and channel pricing separately
View details ↗No matching models
Adjust provider, category or input/output filters. New models are added continuously.
COST EXPLORER
Great models. Clear costs.
Adjust monthly token usage to compare estimated API costs.
1 M = 1 million tokens · USD
Compares base text-token rates within the same channel
Compares base text-token rates within the same channel
Uses collected, comparable USD-per-million-token rates. Snapshots exclude cache discounts, tiers, extra reasoning output and taxes. Check current source prices.
MODEL HANDBOOK
Understand before you choose
How should API prices be compared?+
Separate input, output and cache rates, then estimate the same workload. Image, audio and video rates may use items, duration or resolution rather than tokens.
Do open weights mean free commercial use?+
Not necessarily. Check each version’s license, commercial restrictions and policies. Self-hosting also incurs compute and maintenance costs.
Is the top-ranked model the best for me?+
Rankings depend on tasks, versions and methods. Compare accuracy, latency, reliability and costs on your own workload.