Anthropic
Claude Opus 4.7
model
claude-opus-4-7PremiumStableVisionStreamingVisionToolsBatchLong contextUnited States
Context
1.0M
Input / 1M tokens
$5.00
Output / 1M tokens
$25.00
Weighted tokens formula
1× provider × 17× tier
About this model
Claude Opus 4.7
Anthropic's flagship model — Claude Opus 4.7 leads on coding, reasoning, and agentic workflows. Best-in-class for complex multi-step tasks where you need the model to plan, write code, and verify its own work.
Released
2025-04
Training cutoff
2024-11
Parameters
Not disclosed
Best for
Use cases
- ✓Autonomous coding agents (Claude Code, Cline, Cursor)
- ✓Complex research + literature analysis
- ✓Multi-step planning with tool use
- ✓High-stakes content where quality > cost
- ✓Very long context (1M token window)
Strengths
What it does well
- ●Industry-leading on SWE-bench and coding evals
- ●Strong refusal calibration — minimal over-refusal
- ●1M-token context window
- ●Prompt caching cuts repeat-prompt cost by 90%
- ●Vision + tool calling + structured output all native
Limitations
Know the trade-offs
- !Premium pricing — best for high-value workloads only
- !Higher latency than Sonnet/Haiku — plan for 3-8 s typical
- !Output tokens charged at premium rate — set max_tokens carefully
Code example
Chat completion with Claude Opus 4.7
from openai import OpenAI
client = OpenAI(
base_url="https://api.anoman.io/v1",
api_key="anm-sk-..."
)
response = client.chat.completions.create(
model="claude-opus-4-7",
messages=[{"role": "user", "content": "Hello!"}]
)
print(response.choices[0].message.content)Weighted tokens
weighted_tokens = raw_tokens × 1 (provider) × 17 (tier)
Pro plan: 20M weighted tokens/month. Combined multiplier 17×: 1,176,471 raw tokens available.
Alternatives
Similar models in our catalog
Workloads that fit Claude Opus 4.7 often fit these too. Compare benchmarks and pricing before locking in a default.