Anthropic Claude Fable 5 & Mythos 5: 双轨发布背后的技术革命与安全博弈

// Go: Benchmark comparison
package main
import "fmt"
type Model struct { Name string; SWE, FC, EB, USAMO float64 }
func main() {
    ms := []Model{
        {"Fable 5", 80.3, 29.3, 0, 97.6},
        {"Mythos 5", 80.3, 29.3, 78, 97.6},
        {"Opus 4.8", 69.2, 13.4, 40, 85},
        {"GPT-5.5", 58.6, 5.7, 35, 80},
        {"Gemini 3.1P", 54.2, 0, 30, 70},
    }
    fmt.Printf("%-12s %-10s %-10s %-10s %-8s\n","Model","SWE-Bench","Frontier","Exploit","USAMO")
    for _, m := range ms {
        fmt.Printf("%-12s %-8.1f%%  %-8.1f%%  %-8.1f%%  %-5.1f%%\n", m.Name, m.SWE, m.FC, m.EB, m.USAMO)
    }
}

# Python: Classifier routing simulation
class SafetyClassifier:
    def __init__(self):
        self.thresholds = {"cyber": 0.75, "bio": 0.70, "distill": 0.80}
    def classify(self, prompt):
        pl = prompt.lower()
        scores = {
            "cyber": min(sum(1 for k in ["exploit","vuln","overflow"] if k in pl)/3*1.5, 1.0),
            "bio": min(sum(1 for k in ["pathogen","toxin","weapon"] if k in pl)/3*1.5, 1.0),
            "distill": min(sum(1 for k in ["weights","extract","distill"] if k in pl)/3*1.5, 1.0),
        }
        max_d = max(scores, key=scores.get)
        return (max_d, scores[max_d], scores[max_d] >= self.thresholds[max_d])

c = SafetyClassifier()
for p in ["Write a sort function", "Explain buffer overflow exploit"]:
    d, s, t = c.classify(p)
    print(f"{p[:40]} -> {d}: risk={s:.2f}, fallback={t}")

# Python: Adaptive Thinking simulation
import math
class AdaptiveEngine:
    def complexity(self, text):
        lf = min(len(text)/1000, 1.0)
        cd = sum(1 for m in ["```","def ","class ","import "] if m in text)/4
        rd = sum(1 for k in ["prove","proof","explain","derive","optimize"] if k in text.lower())/5
        return 1.0/(1.0+math.exp(-5.0*(0.25*lf+0.35*cd+0.40*rd-0.4)))
    def think(self, q):
        c = self.complexity(q)
        b = int(256 + c * (8192-256))
        b = ((b+63)//64)*64
        m = "direct" if c<0.3 else "standard" if c<0.7 else "deep"
        return {"complexity": round(c,3), "budget": b, "mode": m}

e = AdaptiveEngine()
for q in ["Capital of France?", "Implement Raft consensus in Go"]:
    r = e.think(q)
    print(f"{q[:40]} -> c={r['complexity']:.3f}, mode={r['mode']}, budget={r['budget']}")

// Go: Migration cost analysis
package main
import ("fmt"; "math")
func main() {
    lines, team := 50_000_000.0, 8
    days := lines/100000 * 0.85 * math.Log2(lines/10000)
    if days > 60 { days = 60 }
    hours := lines/5000000 * (1.0/0.803) * 24 * (1.0-(0.803-0.7))
    costM := days/22 * 20000 * float64(team)
    costAI := (lines*8/1000000)*10 + (lines*8/1000000*0.5)*50
    fmt.Printf("Manual: %.1f days ($%.0f)\n", days, costM)
    fmt.Printf("AI: %.1f hours ($%.0f)\n", hours, costAI)
    fmt.Printf("Speedup: %.1fx, Cost ratio: 1:%.0f\n", days*24/hours, costM/costAI)
}

import anthropic
client = anthropic.Anthropic()

response = client.messages.create(
    model="claude-fable-5", max_tokens=1024,
    thinking={"type": "adaptive"},
    messages=[{"role":"user","content":"Binary search in Python"}],
)
print(response.content[0].text)

# With server-side fallback
response = client.beta.messages.create(
    model="claude-fable-5", max_tokens=1024,
    messages=[{"role":"user","content":"Buffer overflow explanation"}],
    betas=["server-side-fallback-2026-06-01"],
    fallbacks=[{"model":"claude-opus-4-8"}],
)
print(f"Served by: {response.model}")

package main
import (
    "context"; "fmt"; "io"; "log"; "os"
    "github.com/anthropics/anthropic-sdk-go"
    "github.com/anthropics/anthropic-sdk-go/option"
)
func main() {
    c := anthropic.NewClient(option.WithAPIKey(os.Getenv("ANTHROPIC_API_KEY")))
    s := c.Messages.NewStreaming(context.Background(),
        anthropic.MessageNewParams{
            Model: anthropic.F("claude-fable-5"),
            MaxTokens: anthropic.Int(4096),
            Thinking: &anthropic.ThinkingParam{Type: anthropic.F(anthropic.ThinkingTypeAdaptive)},
            Messages: []anthropic.MessageParam{
                anthropic.NewUserMessage(anthropic.NewTextBlock("Explain adaptive thinking"))}})
    defer s.Close()
    for {
        e, err := s.Recv()
        if err == io.EOF { break }
        if err != nil { log.Fatal(err) }
        if ev, ok := e.AsAny().(anthropic.ContentBlockDeltaEvent); ok {
            if ev.Delta.Type == anthropic.ContentBlockDeltaEventDeltaTypeTextDelta {
                fmt.Print(ev.Delta.Text) }}}
}