ByteDance Seed 2.1 Turbo
ByteDance's fast Seed 2.1 reasoning model with a 256K context and output window, native tool calling and image input.
Seed 2.1 Turbo is a cloud text model built by ByteDance. It is multimodal: alongside a text prompt it accepts images, then replies with generated text. Its context window handles up to 262K input tokens and up to 236K output tokens, and it supports adjustable reasoning effort for harder problems. Generation can be tuned with system instructions, temperature, and top-p sampling. It runs through OpenRouter and ByteDance using your own API key, from $0.50 per million input tokens.
- Released
- 3 months ago (Jun 2026)
- Pricing
- $0.50 / 1M in · $2.50 / 1M out
- Inputs
- Text, Images
- Context window
- 262K in · 236K out
- Reasoning
- Adjustable effort
- Controls
- System prompt, Temperature, Top-p
Examples
Generated with Seed 2.1 Turbo via OpenRouter. The same three prompts run against every text model in the catalog, shown verbatim, so the only thing that changes between two models’ answers is the model.
Explain what an API is to someone who has never written code. Do not use a restaurant or waiter analogy. Plain prose only — no headings, bullet points, or markdown formatting. Maximum 50 words.
An API is a set of simple, standard rules that lets separate apps and programs share specific data or features without changing how either works, which is why your phone’s weather app can pull updates from a weather service.
A two-person startup is deciding whether to build their own user authentication or use a hosted provider. Give them a clear recommendation, then the single strongest argument against your own recommendation. Plain prose only — no headings, bullet points, or markdown formatting. Maximum 150 words.
The two-person startup should use a hosted user authentication provider. Their most scarce resource is focused engineering time, and building auth from scratch requires navigating complex compliance rules, password reset flows, multi-factor authentication, and breach response protocols—work that would eat weeks they could instead spend building the unique core product features that actually attract and retain users, with no competitive upside to building auth in-house. The strongest argument against this recommendation is that hosted auth providers charge per-user fees that scale quickly as the startup grows, often costing far more long-term than maintaining a simple in-house system, and vendor outages or sudden policy changes can lock users out of the product with no immediate fix the team can deploy on their own.
Write a briefing for a non-technical executive explaining why their company's spending on AI is hard to predict, and what they can do about it. Cover at least three distinct causes. Plain prose only — no headings, bullet points, or markdown formatting. Write exactly 205 words.
Most companies struggle to forecast AI spending for three key reasons unique to the technology, even if you’re used to predictable software budgets. First, AI runs on shared, high-demand computing hardware rather than fixed licensed software, so costs spike unexpectedly when customer or employee usage surges, or when cloud providers raise prices for the specialized chips AI requires, with no long-term contract lock-in to stabilize rates. Second, AI models degrade over time as real-world data shifts, requiring unplanned fine-tuning, new training data purchases, or full model replacements that rarely show up in initial budget plans, especially as teams test new use cases mid-year. Third, most AI vendors use opaque, usage-based pricing tied to granular metrics like the length of text or images processed, rather than per-user seats, making it hard to map spending to headcount or customer volume the way you would with standard business tools. To rein in unpredictability, start by capping usage for non-critical AI tools, require cross-functional approval for new AI deployments, and negotiate volume discounts or fixed-price contracts for your highest-priority AI use cases, while setting aside a 15 to 20 percent contingency fund for unplanned model updates or compute cost shifts that no amount of upfront planning can fully avoid.
ByteDance
ByteDance's AI labs ship the Seedream image models and the Seedance video models, among other Doubao-branded research.
www.bytedance.com ↗