Compare Speech-to-Text APIs and Transcription Pricing

Google: Gemini 2.5 Flash Lite

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Gemini 2.5 Flash-Lite is Google's lightweight and cost-efficient reasoning model in the Gemini 2.5 family, optimized for high-throughput, low-latency workloads. It supports multimodal inputs including text, images, audio, video, and PDFs, with optional thinking for applications that need a balance between speed, cost, and reasoning quality.

Google: Gemini 3.1 Flash-Lite

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Gemini 3.1 Flash-Lite is Google's low-latency, cost-effective multimodal model optimized for high-frequency and high-volume workloads. It supports text, image, video, audio, and PDF inputs and is designed for lightweight reasoning, data extraction, agentic workflows, tool use, and applications where latency and API cost are primary considerations.

Google: Gemini 2.5 Flash

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Gemini 2.5 Flash is Google's high-performance multimodal workhorse model designed for reasoning, coding, mathematics, science, document understanding, and agentic applications while maintaining Flash-tier speed and cost efficiency.

Google: Gemini 3.5 Flash Lite

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Gemini 3.5 Flash Lite is Google's high-efficiency multimodal model with upgraded agentic capabilities, optimized for low-cost, high-volume workloads and focused subagents operating inside complex multi-agent systems.

Google: Gemini 3.6 Flash

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Gemini 3.6 Flash is a frontier-class Google multimodal Flash model designed for fast reasoning, coding, multimodal understanding, tool use, and scalable agentic applications while retaining Flash-tier latency and efficiency.

Google: Gemini 3.7 Flash

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Gemini 3.7 Flash is a frontier-class Google Flash model focused on high-performance reasoning, coding, multimodal understanding, tool use, and agentic execution with the latency and cost characteristics of the Flash family.

Google: Gemini 3.8 Flash

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Gemini 3.8 Flash is Google's most intelligent Flash model, engineered for long-horizon software engineering, autonomous agents, complex enterprise workflows, advanced reasoning, and multimodal understanding. Building on Gemini 3.7 Flash, it delivers substantial improvements across coding, agentic tasks, and critical multi-step reasoning while retaining Flash-level speed and cost efficiency. It supports a 1M-token context window, configurable thinking levels, function calling, computer use, code execution, search grounding, structured outputs, file search, and URL context.

Meta: Muse Spark 1.1

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Muse Spark 1.1 is Meta's flagship proprietary multimodal frontier model developed by Meta Superintelligence Labs (MSL). Designed for complex reasoning and agentic tasks, it can actively manage a 1-million-token context window, orchestrate multi-agent systems, and natively process text, image, video, and audio inputs. It excels at long-horizon software development, tool use, and computer-use workflows.

Meta: Muse Spark 1.2

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Muse Spark 1.2 is a proprietary coding-focused frontier model developed by Meta Superintelligence Labs. Co-trained specifically with the Muse Code terminal agent, it features significant improvements in code generation, complex debugging, codebase understanding, and end-to-end developer workflows. It leverages planning, goal conditioning, and context compaction to sustain progress on long-horizon tasks like whole-repository generation and GPU kernel optimization.

Google: Gemini 3.5 Flash

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Gemini 3.5 Flash is Google's high-efficiency multimodal model offering near-Pro-level coding and reasoning at Flash-tier speed and cost. It is optimized for coding, parallel agentic execution, multimodal understanding, and scalable production workloads.

Google: Gemini 2.5 Pro

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Gemini 2.5 Pro is Google's advanced Gemini 2.5 reasoning model for complex problem solving, coding, mathematics, scientific analysis, long-context understanding, multimodal reasoning, and sophisticated agentic workflows.

Google: Gemini 3.1 Pro

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Gemini 3.1 Pro is Google's advanced intelligence model for complex reasoning, problem solving, software engineering, multimodal analysis, long-context tasks, and powerful agentic and vibe-coding workflows.

Fishaudio: S2 Pro

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Fish Audio S2 Pro is an advanced 4B parameter open-weight text-to-speech model built on a dual-autoregressive architecture. It supports approximately 80 languages and introduces fine-grained, word-level inline tag control, allowing users to embed open-ended natural language instructions inside square brackets directly in the script (e.g., [whispering], [pitch up]). It outputs 44.1 kHz audio and natively supports zero-shot voice cloning from a reference clip.

Sarvam AI: Saaras V3

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Saaras v3 is a state-of-the-art speech recognition and translation model. It natively supports streaming for real-time applications and features specialized modes for transcription, direct-to-English translation, and transliteration. It is specifically tuned for noisy environments and complex code-mixed (e.g., Hindi-English) speech.

Sarvam AI: Saarika V2.5

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Saarika v2.5 is Sarvam AI's legacy speech recognition model designed for Indian languages and accents. It transcribes audio in the same language spoken, excelling in multi-speaker conversations, telephony audio (8kHz), and code-mixed speech. Supports 11 languages (Hindi, Bengali, Gujarati, Kannada, Malayalam, Marathi, Odia, Punjabi, Tamil, Telugu, English) with automatic language detection and speaker diarization. Achieves 4.96% CER and 18.32% WER on VISTAAR benchmark.