DeepStart | Production-Ready Machine Learning Models | DeepInfra

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Featured models

What we loved, used, and implemented most last month

text-generation

Nemotron-3-Nano-Omni-30B-A3B-Reasoning

nvidia/Nemotron-3-Nano-Omni-30B-A3B-Reasoning cover image

Nemotron 3 Nano Omni is an open multimodal model built on a hybrid Mixture-of-Experts (MoE) architecture, engineered for high efficiency and strong accuracy across image, video, audio, and text inputs. It powers always-on sub-agents for computer use, document intelligence, and audio-video understanding—replacing fragmented vision, speech, and language pipelines with a single unified inference pass.

$0.20 in, $0.80 out / 1M

text-generation

DeepSeek-V4-Pro

deepseek-ai/DeepSeek-V4-Pro cover image

DeepSeek V4 Pro is an MoE model with 1.6T total parameters (49B active) and a 1M-token context window. It's built for advanced reasoning, coding, and long-running agent tasks, and performs well on knowledge, math, and software engineering benchmarks.

$0.145 cached, $1.74 in, $3.48 out / 1M

text-generation

DeepSeek-V4-Flash

deepseek-ai/DeepSeek-V4-Flash cover image

DeepSeek V4 Flash is an efficiency-focused MoE model with 284B total parameters (13B active) and a 1M-token context window. It's tuned for fast inference and high-throughput use cases while still holding up on reasoning and coding tasks.

$0.028 cached, $0.14 in, $0.28 out / 1M

text-generation

moonshotai/Kimi-K2.6 cover image

Kimi K2.6 is an open-source, native multimodal agentic model that advances practical capabilities in long-horizon coding, coding-driven design, proactive autonomous execution, and swarm-based task orchestration.

$0.15 cached, $0.75 in, $3.50 out / 1M

text-generation

Qwen3.6-35B-A3B

Qwen/Qwen3.6-35B-A3B cover image

Qwen3.6-35B-A3B is Alibaba's latest flagship Mixture-of-Experts model, with 35B total parameters and only 3B activated per token (256 experts, 8 routed + 1 shared). Built on direct feedback from the community, Qwen3.6 prioritizes stability and real-world utility, offering developers a more intuitive, responsive, and genuinely productive coding experience.

$0.15 in, $0.95 out / 1M

text-generation

zai-org/GLM-5.1 cover image

GLM-5.1 is Z-AI's next-generation flagship model for agentic engineering, with significantly stronger coding capabilities than its predecessor. It achieves state-of-the-art performance on SWE-Bench Pro and leads GLM-5 by a wide margin on NL2Repo (repo generation) and Terminal-Bench 2.0 (real-world terminal tasks).

$0.205 cached, $1.05 in, $3.50 out / 1M

text-generation

stepfun-ai/Step-3.5-Flash cover image

Step 3.5 Flash is an open-source reasoning model by StepFun with 196B total parameters (11B active) using Mixture of Experts. It features a 256K context window, deep reasoning, tool calling, and agentic capabilities, achieving 97.3 on AIME 2025 and 74.4% on SWE-bench Verified.

$0.02 cached, $0.10 in, $0.30 out / 1M

text-generation

Qwen3.5-397B-A17B

Qwen/Qwen3.5-397B-A17B cover image

Qwen3.5-397B-A17B is Alibaba's most capable Qwen3.5 model, a Mixture-of-Experts architecture with 397B total parameters and 17B activated per token. It features a 262K token context window (extensible to 1M with YaRN), thinking/reasoning mode, tool calling with MCP integration, and support for 201 languages. Sets state-of-the-art results on reasoning, coding, math, and multimodal benchmarks.

$0.54 in, $3.40 out / 1M

text-generation

gemma-4-26B-A4B-it

google/gemma-4-26B-A4B-it cover image

Efficient, MoE variant of Gemma 4. Gemma is a family of open models built by Google DeepMind. Gemma 4 models are multimodal, handling text and image input and generating text output.

$0.07 in, $0.34 out / 1M

text-generation

google/gemma-4-31B-it cover image

Gemma is a family of open models built by Google DeepMind. Gemma 4 models are multimodal, handling text and image input and generating text output.

$0.13 in, $0.38 out / 1M

text-generation

Qwen3.5-122B-A10B

Qwen/Qwen3.5-122B-A10B cover image

Qwen3.5-122B-A10B is a large Mixture-of-Experts model from Alibaba's Qwen3.5 series with 122B total parameters and 10B activated per token. It features a 262K token context window (extensible to 1M with YaRN), thinking/reasoning mode, tool calling, and support for 201 languages. Excels at complex reasoning, coding, multimodal understanding, and agentic tasks with the efficiency of sparse activation.

$0.29 in, $2.40 out / 1M

text-generation

NVIDIA-Nemotron-3-Super-120B-A12B

nvidia/NVIDIA-Nemotron-3-Super-120B-A12B cover image

NVIDIA Nemotron 3 Super is a hybrid Mixture-of-Experts (MoE) model engineered for highest compute efficiency and accuracy in multi-agent applications and specialized agentic systems. It is optimized to run many collaborating agents per application on a single GPU, delivering high accuracy for reasoning, tool use, and instruction following.

$0.10 in, $0.50 out / 1M

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Latest Models

zai-org/GLM-4.6 deepseek-ai/DeepSeek-V3.2-Exp deepseek-ai/DeepSeek-V3.1 zai-org/GLM-5.1 anthropic/claude-3-7-sonnet-latest

Featured Models

Qwen/Qwen3-Max deepseek-ai/DeepSeek-V4-Pro Qwen/Qwen3-TTS deepseek-ai/DeepSeek-V3.2 Qwen/Qwen3-TTS-VoiceDesign

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