Dola Seed 2.0 Mini is the smallest member of ByteDance's Dola Seed 2.0 family on BytePlus ModelArk, an omnimodal-understanding deep-thinking model tuned for shorter reasoning traces and higher token efficiency.
- Input
- text image video audio $0.1/M
- Output
- text $0.4/M
- Cache read
- $0.02/M
- Context
- 262K
- vs GPT-4o
- ~98% cheaper
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-mini (latest version 260428)
- 256K context, 128K max output incl. CoT
- audio understanding in beta on the 260428 version
- implicit + explicit context caching
Use Dola Seed 2.0 Mini 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-mini",
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-mini",
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-mini",
"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-mini",
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-mini")
.addUserMessage("Summarize this diff")
.build());
System.out.println(resp.choices().get(0).message().content().orElse(""));About Dola Seed 2.0 Mini
- Official release notes position it for low-latency, high-concurrency, cost-sensitive scenarios that emphasize fast responses and flexible deployment for inference, which is the line for choosing it over Lite when throughput matters more than depth.
- It carries a 256K context window with up to 128K output including chain-of-thought, and supports deep reasoning, multimodal understanding, function calling with MCP tool integration, structured output, thinking summaries, and prefix or session caching in both implicit and explicit forms.
- Like the rest of the family it takes text, image, and video, with audio understanding listed for the newest build, and returns text only.
- Thinking is controlled by thinking.type with just enabled and disabled, no automatic mode, and is on by default; reasoning_effort sets the depth at minimal, low, medium, or high, defaulting to medium, so a Mini deployment chasing latency should usually pin it lower rather than accept the default.
- Max output defaults to 4K regardless of the 128K ceiling, and BytePlus publishes no per-model documentation page for the 2.0 family, so release notes and the capability matrix are the authoritative source.
- Synthorai presents it through an OpenAI-compatible chat completions API.
FAQ
Is the Dola Seed 2.0 Mini API free to try?
Yes: new accounts get 10 trial calls and up to $1 in free credit, no card required. At $0.1/M input tokens, that credit alone covers roughly 1,250 requests of ~8K tokens against Dola Seed 2.0 Mini.
What is Dola Seed 2.0 Mini best at?
Shorter reasoning traces, higher token efficiency; built for low-latency, cost-sensitive scenarios; deep reasoning with prefix or session caching. See the About section for the full picture from the vendor's own release notes.
How much does Dola Seed 2.0 Mini cost?
Dola Seed 2.0 Mini costs $0.1 per million input tokens and $0.4 per million output tokens on Synthorai. That is the provider's list price, with no platform markup. Cached input tokens bill at $0.02/M.
Does Dola Seed 2.0 Mini support prompt caching?
Yes: automatic caching is on by default, with an explicit mode for guaranteed savings. Cached input tokens bill at $0.02/M vs $0.1/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 Mini?
Point your existing OpenAI SDK at base_url="https://synthorai.io/v1", set model="Dola-Seed-2.0-mini", 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.