Claude Fable 5.1 vs Qwen3.8 Max
Claude Fable 5.1 is served by invitation. Its figures below are the live rates, but calls need a workspace grant first; ask us for access before you build on this comparison.
Which one, when
Both take text and image in and return text, share a $0.25 cache-read rate, and sit within a rounding error of each other on capacity - 1000000 tokens of context and 128000 max output for claude-fable-5-1 against 983616 and 131072 for qwen3.8-max. The separation is the rate card: qwen3.8-max costs $2 input and $6 output versus $10 and $50, so claude-fable-5-1 is 5x the input and just over 8x the output price, which matters most on long generations. Pick claude-fable-5-1 when you want its always-on thinking mode, and qwen3.8-max for high-volume work at a fraction of the cost.
Benchmarks
Vendor-published: Alibaba (Qwen) Anthropic ByteDance DeepSeek Google MiniMax Moonshot OpenAI Tencent Z.ai
Pricing
| Claude Fable 5.1 | Qwen3.8 Max | Δ | |
|---|---|---|---|
| Input / 1M tokens | $10 | $2 | 5× |
| Output / 1M tokens | $50 | $6 | 8.3× |
| Cache read / 1M tokens | $0.25 | $0.25 | = |
| Cache write | 1.25x (5m) / 2x (1h) | 1.25x | - |
Rates from the live catalog at build time; each model page carries the current card.
Where they sit - input price per 1M tokens across all 67 chat models on this billing unit (log scale)
Capabilities
| Claude Fable 5.1 | Qwen3.8 Max | |
|---|---|---|
| Tool use | yes | yes |
| Thinking control | always on | yes - vendor dial not published |
| Structured output | yes | yes |
| Prompt caching | explicit (you mark the prefix) | implicit + explicit |
| Cache lifetime | 5m default, 1h option | explicit: 5m, reset on hit |
| Minimum cached prefix | 1024 tokens | 1024 tokens |
Specs
| Claude Fable 5.1 | Qwen3.8 Max | |
|---|---|---|
| Input modalities | text image | text image |
| Output modalities | text | text |
| Released | 2026-09-01 | 2026-08-03 |
| Knowledge cutoff | 2026-06 | - |
| Context window | 1M | 984K |
| Max output | 128K | 131K |
| Thinking parameter | output_config.effort (thinking is adaptive-only and always on) | - |
| Accepted values | effort
| - |
| Default | thinking always on (adaptive) effort
| - |
Specs are transcribed from each vendor’s documentation; a row a vendor does not publish is left out rather than inferred. Full sources: Claude Fable 5.1 · Qwen3.8 Max
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="claude-fable-5-1",
# model="qwen3.8-max", # uncomment this line, comment the one above
messages=[{"role": "user", "content": "Summarize this diff"}],
reasoning_effort="medium",
)
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: "claude-fable-5-1",
// model: "qwen3.8-max", // uncomment this line, comment the one above
messages: [{ role: "user", content: "Summarize this diff" }],
reasoning_effort: "medium",
});
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": "claude-fable-5-1",
# "model": "qwen3.8-max", # uncomment this line, comment the one above
"messages": [{"role": "user", "content": "Hello"}],
"reasoning_effort": "medium"
}'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: "claude-fable-5-1",
// Model: "qwen3.8-max", // uncomment this line, comment the one above
Messages: []openai.ChatCompletionMessageParamUnion{
openai.UserMessage("Summarize this diff"),
},
ReasoningEffort: openai.ReasoningEffortMedium,
})
fmt.Println(resp.Choices[0].Message.Content)
}import com.openai.client.OpenAIClient;
import com.openai.client.okhttp.OpenAIOkHttpClient;
import com.openai.models.chat.completions.*;
import com.openai.models.ReasoningEffort;
OpenAIClient client = OpenAIOkHttpClient.builder()
.baseUrl("https://synthorai.io/v1")
.apiKey("sk-syn-...")
.build();
ChatCompletion resp = client.chat().completions().create(
ChatCompletionCreateParams.builder()
.model("claude-fable-5-1")
// .model("qwen3.8-max") // uncomment this line, comment the one above
.addUserMessage("Summarize this diff")
.reasoningEffort(ReasoningEffort.MEDIUM)
.build());
System.out.println(resp.choices().get(0).message().content().orElse(""));FAQ
Which is cheaper, Claude Fable 5.1 or Qwen3.8 Max?
Qwen3.8 Max is cheaper on input / 1m tokens ($2 vs $10, 5.0× apart). Other rows may point the other way - the table above carries the full card, and real cost depends on your mix.
Can I A/B test Claude Fable 5.1 against Qwen3.8 Max without two integrations?
Yes. Both are served through the same OpenAI-compatible endpoint with one API key - switching is a one-line model-string change, so you can route a fraction of traffic to each and compare bills directly.
Do Claude Fable 5.1 and Qwen3.8 Max support prompt caching?
Yes - both bill cached 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.