Seed 1.6 Flash / 채팅
Compared with the flash-0615 version, the 0715 version has achieved a nearly 10% significant improvement in the performance of pure text tasks under both thinking and non-thinking
Playground Chat
AI 모델과 대화를 시작하세요. 무엇이든 질문할 수 있습니다.
AI가 생성한 응답의 정확성은 다를 수 있습니다.
Seed 1.6 FlashInstant Responses for Interactive Apps
Seed 1.6 Flash prioritizes first-token latency while keeping full thinking, effort, tool, and sampling controls for responsive product surfaces.
At a Glance
Speed Without Sacrificing Controls
The same control surface, tuned for interactive speed.
Flash Inference Path
Latency-optimized path for snappy chat, autocomplete, and inline assistants.
Optional Thinking
Disable thinking for maximum speed or enable it with minimal effort for light reasoning.
Streaming Native
stream defaults to true so UIs paint tokens as they arrive.
Full Tool Surface
Parallel tool calling and stop sequences remain available at flash speeds.
How It Works
A production-ready path from brief to finished asset.
Stream Immediately
Start rendering tokens as soon as the first chunk arrives.
Prefer Minimal Effort
Keep reasoning Minimal for autocomplete, rewrites, and short answers.
Disable Thinking if Needed
Turn thinking off entirely when you need the lowest possible TTFT.
Escalate Selectively
Raise effort only for the subset of turns that truly need deeper analysis.
Interactive Product Domains
Where perceived latency is UX.
Inline Autocomplete
Sub-second completions inside editors.
Chat Widgets
Streaming replies for support surfaces.
Search Q&A
Fast answers over retrieved context.
Voice Turn-Taking
Low latency for conversational agents.
Prompt & Usage Tips
Practical guidance for reliable first-pass results.
Flash shines on concise instructions. Long multi-constraint prompts can slow useful output.
Autocomplete, side-panel rewrites, and quick Q&A are the sweet spot.
Route proofs and long analyses to Seed 1.6 / 1.8 / 2.0 Pro.
Flash Quickstart
Low-latency streaming chat.
curl -X POST "https://api.powertokens.ai/v1/chat/completions" \
-H "Authorization: Bearer YOUR_API_KEY" \
-H "Content-Type: application/json" \
-d '{
"model": "seed-1-6-flash-250715",
"messages": [
{"role": "user", "content": "Rewrite this product blurb in a friendlier tone."}
],
"stream": true,
"temperature": 0.7
}'Technical Specifications
Confirmed parameters and runtime execution protocols.
가격 상세
이 모델의 실제 요금은 API 요청에서 전달된 특정 매개변수를 기반으로 동적으로 계산됩니다. 아래는 구체적인 조합과 해당 가격입니다:
| 모달리티 | 입력 크레딧 | 출력 크레딧 | 입력 가격 | 출력 가격 | 암시적 캐시 적중 | 명시적 캐시 적중 | 캐시 생성 |
|---|---|---|---|---|---|---|---|
| 0 - 128K | 71/ 1M Tokens | 285/ 1M Tokens | $0.071 | $0.285 | $0.015 15/ 1M Tokens | -- | -- |
| 128K - 256K | 95/ 1M Tokens | 760/ 1M Tokens | $0.095 | $0.760 | $0.015 15/ 1M Tokens | -- | -- |
Models from the Same Channel
Explore complementary models and alternative versions from the same provider channel.
DeepSeek-V4.1-Flash
deepseek-v4-1-flash-260910
Lightweight flagship of DeepSeek's new Causal Encoder-Decoder family. 552B-parameter MoE with asymmetric activation—8B for input, 16B for output—delivering flagship-level intelligence at significantly lower inference cost . Native multimodal vision understanding. 1M-token context window with 384K max output. KV cache compressed to 1/4 HBM and 1/8 SSD of previous generation . Outperforms V4-Pro on Terminal-Bench 2.1 (90.6), DeepSWE v1.1 (74.2), and CyberGym (88.1)
DeepSeek V3.2
deepseek-v3-2-251201
The official version of DeepSeek-V3.2 balances reasoning capability and output length, making it suitable for daily use—such as question-answering scenarios and general Agent task scenarios.
Seed 2.0 Pro
seed-2-0-pro-260328
Focused on long-chain reasoning and stability in complex task execution, designed for complex real-world business scenarios.
Seed 2.0 Lite
seed-2-0-lite-260228
Balances generation quality and response speed, making it a strong general-purpose production model.
Recommended Related Models
Explore complementary video and multimodal models with your unified API key.
GLM-5.3
glm-5.3
Zhipu AI's flagship text model optimized for complex software engineering and long-horizon Agent tasks. Features a 1M-token context window with mandatory reasoning (3 levels: low/high/max). Coding capability improved 50% over GLM-5.2 on Z.ai Code Bench; scores SOTA on Terminal Bench 3.0. Excels in cybersecurity tasks (cyber vulnerability discovery)
MiniMax-M3.1-Flash
MiniMax-M3.1-Flash
Next-gen efficiency-focused multimodal model (428B MoE) for agentic workflows, coding, and computer use . Features a 1M-token context window and tunable thinking depth (low–max) . Scores 73.7% on DeepSWE v1.1, 61.7 on OSWorld V2, and 82% on CyberGym, while delivering 200+ TPS output speed at 70% lower agent-task cost than its predecessor
GLM-5.3 Flash
glm-5.3-flash
Z.ai's native multimodal model (320B-A18B) with text, image, video, and file input. Features hybrid sparse + linear attention, reducing attention compute 3x and KV cache 4.4x vs. GLM-5.3. Scores 57 on Artificial Analysis Intelligence Index—matching Claude Opus 4.8—with 1M context and 128K max output. Excels in agentic coding, vision-based Computer Use, and CAD reproduction
Qwen3.8 Flash
qwen3.8-flash
Alibaba's cost-efficient multimodal reasoning model. Supports text, image, and video inputs with text output. Features a native 1M-token context window for long documents, codebases, and agentic workflows. Excels in coding assistance, desktop interaction, chart analysis, and long-video understanding. Compatible with OpenAI/Anthropic protocols for seamless integration
Frequently Asked Questions
Everything you need to know before integrating this model.
Start Building with Seed 1.6 Flash Today
Create an account in seconds to receive free test credits. No upfront payment or long-term contract required.