Dola Seed 2.0 Lite is the balanced tier of ByteDance's Dola Seed 2.0 family on BytePlus ModelArk.
- Input
- text image video audio $0.25/M
- Output
- text $2/M
- Cache read
- $0.05/M
- Context
- 262K
- vs GPT-4o
- ~95% cheaper
Benchmarks
Vendor-published: Alibaba (Qwen) Anthropic ByteDance Google MiniMax Moonshot OpenAI Tencent Z.ai
Price in context
Where the price sits among 60 comparable models
The bar shows how this model’s price compares with every other model of the same kind on Synthorai. The cheapest and the most expensive are named at each end. These are base rates; batch, region and cache-write discounts are on the pricing page.
Specs & limits
Tokens
| Context window (vendor spec) | 256,000 |
|---|---|
| Max output (vendor spec) | 131,072 |
Prompt caching
| How it caches | automatic + explicit |
|---|---|
| Min prefix | 1,024 |
Thinking
| Vendor control | thinking.type + reasoning_effort |
|---|---|
| Accepted values | thinking.type enabled · disabled (no auto); reasoning_effort minimal · low · medium · high |
| Default | enabled, with reasoning_effort medium applied when the request sets nothing |
| Can be turned off | Yes |
| Thinking behaviour | Trace returns in reasoning_content and is kept in the conversation history; on tool-calling turns nothing must be passed back, and no error is raised if it is omitted. |
| Parameter | reasoning_effort |
| Values | minimal · low · medium · high the gateway's parameter surface - the vendor mapping above applies |
Model
| Modalities | text + image + video + audio → text |
|---|
- Seed 2.0 series launched 2026-02-14
- ModelArk id seed-2-0-lite (latest version 260428)
- 256K context, 128K max output incl. CoT
- audio understanding in beta on the 260428 version
- implicit + explicit context caching
One prompt, measured through the gateway
Dola Seed 2.0 Lite passed · 3 sentences
Enabling reasoning on our production LLM requires the model to run resource-intensive multi-step chain-of-thought inference for every customer-facing query, rather than the single-pass inference that powered our original non-reasoning deployment, and GPU compute—which makes up 90% of our total LLM bill—scales directly with the number of compute cycles each query consumes. Our cloud provider’s LLM billing model charges per million processed tokens, and reasoning workflows generate an average of 2.1x more hidden processing tokens (the intermediate problem-solving steps the model never surfaces to end users) that are still billable, pushing our total monthly token consumption just over double what it was prior to enabling the feature. […]
out 1306 tok (+1096 thinking) latency 18.2 s
Instruction following (exactly three sentences - countable), audience shaping (CFO register), and the hidden-thinking billing gap the token meters below expose.
Dola Seed 2.0 Lite passed · 8/8 cases
### Corrected Function ```python def longest_run(xs): if not xs: # Handle empty input edge case return 0 best = cur = 1 # Base run length of 1 for any non-empty single element for i in range(1, len(xs)): if xs[i] == xs[i - 1]: cur += 1 best = max(best, cur) else: cur = 1 # Reset run length for the new, different element return best ``` ### Bug Explanation (single paragraph) The original function’s core flaw was that it counted the number of consecutive equal adjacent element pairs, rather than the number of elements in the run itself, leading to all results being off by one, which caused both reported issues: a run of k equal elements only has k-1 consecutive matching pairs, so the original function’s maximum `best` value was always one less than the true element count of the longest run. […]
out 2620 tok (+2217 thinking) latency 33.2 s
Whether the fix is actually correct (runnable), explanation density, and token efficiency on a bounded task.
Dola Seed 2.0 Lite passed · 5/5 fields, guidance "Formal guidance withheld pending Q4 clos"
{ "company": "Meridian Robotics", "quarter": "September quarter", "revenue_usd_m": 412, "growth_pct": 11, "guidance": "Formal guidance withheld pending Q4 close" }
out 1502 tok (+1439 thinking) latency 20.2 s
Schema obedience (no invented fields), hallucination pressure (guidance is explicitly withheld), and structured-output path differences.
Dola Seed 2.0 Lite missed · 141 words, 0 banned, 1 question
Today we launch Cross-Provider Prompt Cache, a new feature for our Core API Gateway built to cut redundant AI costs and latency for teams routing requests across multiple LLM providers. Many development teams rotate between OpenAI, Anthropic, and Google Gemini to balance performance, cost, and capability, but identical prompts get reprocessed from scratch with every provider switch, wasting tokens and slowing response times. This feature stores validated prompt responses at the gateway layer, so repeat requests pull from cache regardless of which provider they route to, with configurable TTLs and built-in compliance with all major provider data policies. […]
out 1870 tok (+1695 thinking) latency 23.1 s
Constraint obedience (word budget, banned-word list, the single question), style fingerprint, and length control.
Use Dola Seed 2.0 Lite in 30 seconds
OpenAI-compatible: swap the base_url, keep your SDK. POST /v1/chat/completions
from openai import OpenAI
client = OpenAI(
base_url="https://synthorai.io/v1",
api_key="sk-syn-...",
)
resp = client.chat.completions.create(
model="Dola-Seed-2.0-lite",
messages=[{"role": "user", "content": "Summarize this diff"}],
)
print(resp.choices[0].message.content)import OpenAI from "openai";
const client = new OpenAI({
baseURL: "https://synthorai.io/v1",
apiKey: "sk-syn-...",
});
const resp = await client.chat.completions.create({
model: "Dola-Seed-2.0-lite",
messages: [{ role: "user", content: "Summarize this diff" }],
});
console.log(resp.choices[0].message.content);curl https://synthorai.io/v1/chat/completions \
-H "Authorization: Bearer sk-syn-..." \
-H "Content-Type: application/json" \
-d '{
"model": "Dola-Seed-2.0-lite",
"messages": [{"role": "user", "content": "Hello"}]
}'package main
import (
"context"
"fmt"
"github.com/openai/openai-go/v3"
"github.com/openai/openai-go/v3/option"
)
func main() {
client := openai.NewClient(
option.WithBaseURL("https://synthorai.io/v1"),
option.WithAPIKey("sk-syn-..."),
)
resp, _ := client.Chat.Completions.New(context.TODO(), openai.ChatCompletionNewParams{
Model: "Dola-Seed-2.0-lite",
Messages: []openai.ChatCompletionMessageParamUnion{
openai.UserMessage("Summarize this diff"),
},
})
fmt.Println(resp.Choices[0].Message.Content)
}import com.openai.client.OpenAIClient;
import com.openai.client.okhttp.OpenAIOkHttpClient;
import com.openai.models.chat.completions.*;
OpenAIClient client = OpenAIOkHttpClient.builder()
.baseUrl("https://synthorai.io/v1")
.apiKey("sk-syn-...")
.build();
ChatCompletion resp = client.chat().completions().create(
ChatCompletionCreateParams.builder()
.model("Dola-Seed-2.0-lite")
.addUserMessage("Summarize this diff")
.build());
System.out.println(resp.choices().get(0).message().content().orElse(""));About Dola Seed 2.0 Lite
- BytePlus describes its newest release as the first omnimodal understanding model in the Dola family, natively unifying video, image, audio, and text understanding with upgraded agent, coding, and GUI capabilities; the prior release was billed as a cost-efficient, high-throughput enterprise upgrade over seed-1-8 with strong long-context understanding and reliable structured outputs for core production workflows.
- It offers a 256K context window with up to 128K output including chain-of-thought, double the 64K total output of seed-1.8, which is the concrete reason to move long-reasoning work onto the 2.0 generation.
- Output defaults to 4K, so raise it deliberately for long answers.
- Thinking is on by default through thinking.type, which offers only enabled and disabled with no automatic setting, and reasoning depth is tuned separately through reasoning_effort at minimal, low, medium, or high, defaulting to medium.
- Structured output with a JSON schema, function calling with MCP tool integration, thinking summaries, and both implicit and explicit caching at prefix and session level are supported, and output is text only regardless of what goes in.
- BytePlus publishes no head-to-head selection guide for the family, so the release-note positioning is the official basis for choosing between the tiers.
- Synthorai brokers it through an OpenAI-compatible chat API.
FAQ
Is the Dola Seed 2.0 Lite API free to try?
Yes: new accounts get 10 trial calls and up to $1 in free credit, no card required. At $0.25/M input tokens, that credit alone covers roughly 500 requests of ~8K tokens against Dola Seed 2.0 Lite.
What is Dola Seed 2.0 Lite best at?
First omnimodal understanding model in its family; natively unifies video, image, audio, and text; 256K context with up to 128K output. See the About section for the full picture from the vendor's own release notes.
How much does Dola Seed 2.0 Lite cost?
Dola Seed 2.0 Lite costs $0.25 per million input tokens and $2 per million output tokens on Synthorai. That is the provider's list price, with no platform markup. Cached input tokens bill at $0.05/M.
Does Dola Seed 2.0 Lite support prompt caching?
Yes: automatic caching is on by default, with an explicit mode for guaranteed savings. Cached input tokens bill at $0.05/M vs $0.25/M uncached; prompts need a 1,024-token stable prefix to cache. Prompt caching guide →
How do I get access to Dola Seed 2.0 Lite?
Point your existing OpenAI SDK at base_url="https://synthorai.io/v1", set model="Dola-Seed-2.0-lite", and you're done. One API key covers every model on the gateway.
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Every value on this page is transcribed from the vendor's own documentation, linked above, and carries the date it was checked. Prices are compared across the catalogue; specification values that vendors define differently are shown with the difference stated rather than charted. Nothing here is measured by us, and nothing is scored.