Dola Seed 2.0 Lite vs MiniMax M3
MiniMax M3 has been retired from our catalogue. Its figures below are the last published rates; calls to it are no longer served, while the other model in this comparison is.
Which one, when
Pick Dola-Seed-2.0-lite if you need audio input - it accepts text, image, video and audio, where minimax-m3 stops at video - and its $0.25 input slightly undercuts $0.3. Choose minimax-m3 for long or output-heavy work: a 1000000-token context and 524288 max output, roughly 3.9x and 4x Dola-Seed-2.0-lite's 256000 and 131072, plus reasoning and long-context flags and $1.2 output against $2. Cache reads are near-identical at $0.05 versus $0.06, and both let you disable thinking.
Benchmarks
MiniMax M3: the vendor has not published benchmark scores.
Vendor-published: Alibaba (Qwen) Anthropic ByteDance DeepSeek Google MiniMax Moonshot OpenAI Tencent Z.ai
Pricing
| Dola Seed 2.0 Lite | MiniMax M3 | Δ | |
|---|---|---|---|
| Input / 1M tokens | $0.25 | $0.3 | 0.83× |
| Output / 1M tokens | $2 | $1.2 | 1.7× |
| Cache read / 1M tokens | $0.05 | $0.06 | 0.83× |
| Cache write | - | no separate charge | - |
Rates from the live catalogue at build time; each model page carries the current rate card.
Where they sit · input price per 1M tokens across all 76 chat models on this billing unit (log scale)
Capabilities
| Dola Seed 2.0 Lite | MiniMax M3 | |
|---|---|---|
| Tool calling | yes | yes |
| Thinking control | configurable | configurable |
| Structured output | yes | - |
| Prompt caching | implicit + explicit | implicit (automatic) |
| Cache lifetime | not published | not published |
| Minimum cached prefix | 1024 tokens | 512 tokens |
Specs
| Dola Seed 2.0 Lite | MiniMax M3 | |
|---|---|---|
| Input modalities | text image audio video | text image video |
| Output modalities | text | text |
| Released | 2026-02-14 | 2026-06-01 |
| Context window | 256K | 1M |
| Max output | 131K | 524K |
| Thinking parameter |
|
|
| Accepted values | thinking.type
reasoning_effort
| thinking.type
reasoning_split
|
| Default | enabled, with reasoning_effort medium | adaptive: thinking on, with the model deciding when extra reasoning helps |
Specs are transcribed from each vendor’s documentation; a row a vendor does not publish is left out rather than inferred. Full sources: Dola Seed 2.0 Lite · MiniMax M3
Switch between them with one line
Both ids are in every tab below; the highlighted pair of lines is the only edit. Same endpoint, same key, same request shape.
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",
# model="minimax-m3", # uncomment this line, comment the one above
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",
// model: "minimax-m3", // uncomment this line, comment the one above
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",
# "model": "minimax-m3", # uncomment this line, comment the one above
"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",
// Model: "minimax-m3", // uncomment this line, comment the one above
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")
// .model("minimax-m3") // uncomment this line, comment the one above
.addUserMessage("Summarize this diff")
.build());
System.out.println(resp.choices().get(0).message().content().orElse(""));FAQ
Which is cheaper, Dola Seed 2.0 Lite or MiniMax M3?
Dola Seed 2.0 Lite is cheaper on the "Input / 1M tokens" row ($0.25 vs $0.3, 1.2× apart). Other rows may point the other way; the table above carries the full rate card, and real cost depends on your mix.
Can I A/B test Dola Seed 2.0 Lite against MiniMax M3 without two integrations?
Yes. Both are served through the same OpenAI-compatible endpoint with one API key. Switching is a one-line change to the model id, so you can route a fraction of traffic to each and compare bills directly.
Do Dola Seed 2.0 Lite and MiniMax M3 support prompt caching?
Yes. Both bill cache reads below their input rate, so warm-prefix workloads cost less than the list rates suggest. The exact cache-read rows are in the pricing table above.