LLMAnonymized

Seed 2.1 Turbo

Seed 2.1 Turbo is ByteDance's high-throughput, agent-capable AI model optimized for cost-sensitive production workloads with strong vision and code execution.

Maker
ByteDance
Modality
Text + vision
Context
256K tokens
Open weights
No

Overview

What is Seed 2.1 Turbo

Seed 2.1 Turbo is a proprietary, multimodal AI model released by ByteDance in June 2026 as part of the Seed2.1 family. Designed for real-world productivity, it supports vision, function calling, reasoning, web search, and code-optimized workflows with a 256K context window and low-latency throughput for scalable deployments.

Running it privately on Venice

On Venice, Seed 2.1 Turbo runs with anonymized privacy — your prompts are never stored or profiled. This ensures sovereignty over sensitive workflows while retaining full access to its agent capabilities, including vision and code execution. You get uncensored, permissionless inference without sacrificing compliance or control.

AnonymizedNo prompt trainingTEE · hardware enclaveEnd-to-end encrypted

Assessment

Strengths and limitations

Strengths
  • Optimized for agent workflows with reliable multi-step task execution across tools and environments.
  • Strong multimodal understanding, including accurate processing of complex visual and video content.
  • Efficient code generation and debugging with end-to-end delivery in enterprise development pipelines.
  • High throughput at low cost, ideal for large-scale production use where latency and token economics matter.
  • Supports web search, structured output, and multiple image inputs for rich, dynamic interactions.
Limitations
  • Not open-source or open-weights: cannot be self-hosted or fine-tuned.
  • Lower benchmark performance compared to top-tier models like Claude Opus 5 or GPT-5.6 Luna in most evaluations.
  • No end-to-end encryption or TEE protection on Venice — privacy is anonymized but not encrypted in transit or at rest.

Capabilities

What it supports

  • Tool use / function calling
  • Vision (image input)
  • Reasoning
  • Web search
  • Code-optimized
  • Structured output (JSON schema)
  • Audio input
  • Video input
  • Multiple image inputs
  • Log probabilities

Specifications

Datasheet

Maker
ByteDance
Released
June 24, 2026
Architecture
Proprietary transformer
Parameters
Not publicly disclosed
Open weights
No
Context window
256K tokens
Max output
65.536K tokens
Capabilities
Vision, Function calling, Reasoning, Web search, Code-optimized
Privacy on Venice
Anonymized — prompts not stored
Available on Venice since
Jun 2026
License
Proprietary

API

Call it from your code

Venice exposes an OpenAI-compatible API. Point your base URL at Venice and pass the model id.

curl https://api.venice.ai/api/v1/chat/completions \
  -H "Authorization: Bearer $VENICE_API_KEY" \
  -H "Content-Type: application/json" \
  -d '{
    "model": "seed-2-1-turbo",
    "messages": [{ "role": "user", "content": "Explain quantum tunneling simply." }]
  }'

Pricing

What it costs on Venice

Billed per token on Venice: $0.63 per 1M input tokens and $3.13 per 1M output tokens.

Input / 1M tokens
$0.63
Per 1M tokens
Output / 1M tokens
$3.13
Per 1M tokens
Cached input / 1M
$0.13
Per 1M tokens

New Venice accounts include a free daily allowance and 500 welcome credits — no credit card required.

Alternatives

How it compares

ModelBest forMax contextInput cost / 1MOutput cost / 1MOpen weights
Seed 2.1 TurboBalances vision, code, and agent performance at mid-tier pricing on Venice.256K tokens$0.63 in · $3.13 out / 1M$3.13No
Claude Opus 5Higher cost but stronger raw capability and larger context window.1M tokens$6 in · $30 out / 1M$30.00No
DeepSeek V4 Flash 0731Much cheaper, but lacks vision and advanced agent features.1M tokens$0.17 in · $0.35 out / 1M$0.35No
Google Gemma 4 31B InstructOpen weights and lowest cost, but weaker in vision and agent tasks.256K tokens$0.12 in · $0.36 out / 1M$0.36Yes

Balances vision, code, and agent performance at mid-tier pricing on Venice.

Use cases

What it is good for

  1. 01Automating office workflows with multi-tool orchestration and document processing.
  2. 02Processing long-form visual data such as screenshots, diagrams, and video frames for analysis.
  3. 03Scaling AI agents in customer support, data entry, and internal tooling with low per-token cost.
  4. 04Enterprise software engineering tasks including requirement parsing, implementation, and debugging.
  5. 05Applications requiring vision + web search integration, such as real-time research or content validation.

Prompting

Getting better results

Use clear step-by-step instructions for multi-agent tasks to maximize reliability.

Include image inputs with descriptive captions to improve multimodal reasoning accuracy.

Leverage function calling with explicit JSON schemas for structured data extraction.

Use web search when up-to-date information is required — the model integrates results natively.

Version history

Seed 2.0
2025

Predecessor model

Seed 2.1 Pro
2026-06

Flagship 'deep thinking' variant in the same family

Seed 2.1 Turbo
2026-06

Current — optimized for throughput and cost

FAQ

Frequently asked questions

Seed 2.1 Turbo is a proprietary, multimodal AI model developed by ByteDance, released in June 2026. It is optimized for high-throughput, cost-sensitive production environments requiring vision, code execution, and agent-like task automation with a 256K context window.

On Venice, Seed 2.1 Turbo costs $0.63 per 1M input tokens and $3.13 per 1M output tokens. Cached input is billed at $0.13 per 1M tokens, making repeated queries more efficient.

No. Seed 2.1 Turbo is a proprietary model with closed weights. It is not free to use and cannot be self-hosted or modified. Access is available via API on platforms like Venice.

Yes. Seed 2.1 Turbo supports multimodal input, including multiple images and video frames, with strong spatial and temporal reasoning capabilities for visual analysis tasks.

Yes. Seed 2.1 Turbo supports function calling and tool use, enabling it to execute multi-step workflows, interact with external systems, and return structured outputs via JSON schema.

Seed 2.1 Turbo supports a 256K-token context window, allowing it to process long documents, codebases, and complex multimodal inputs in a single session.

Claude Opus 5 outperforms Seed 2.1 Turbo in most benchmarks and offers a 1M-token context window, but at significantly higher cost. Seed 2.1 Turbo is better suited for budget-conscious deployments needing vision and code integration.

Yes. Seed 2.1 Turbo has built-in web search capabilities, allowing it to retrieve and synthesize up-to-date information during inference, which enhances accuracy for real-time queries.

Run Seed 2.1 Turbo privately

No prompt logging. No data used for training.