Claude Opus 4.7 Migration | 3 Breaking Points from 4.6 and How to Fix Them
For developers who immediately start getting HTTP 400 errors after migrating from Claude Opus 4.6 to 4.7, here is a guide covering the three places where you are guaranteed to get stuck. We walk through removing deprecated parameters like temperature, switching to Adaptive Thinking, and alternatives to prefill deprecation — with Python and TypeScript code diffs — in the order that resolves 400 errors most efficiently.
There are exactly 3 breaking changes in Opus 4.6 → 4.7 that will always return HTTP 400, and none of them are fixed by simply swapping the model ID. Completely removing the 4 parameters — temperature, top_p, top_k, and thinking.budget_tokens — from your request is the starting point for migration.
If you use the thinking feature, Adaptive Thinking is the only option, and you must explicitly set thinking: {type: "adaptive"} + output_config: {effort: "high"}. Since thinking is OFF by default, code that used budget_tokens in 4.6 will not work without rewriting.
Easy to overlook is the increased token consumption from the new tokenizer — up to 1.35× more tokens for the same text, and up to 3× more for images. Leaving max_tokens at the old value will cause truncated responses, so pre-measure with /v1/messages/count_tokens.
目次 (19)
- 3 Places Where You Get Stuck from 4.6 (Guaranteed 400 Errors) + 2 Additional Notes
- Breaking Point 1/3: Sampling Parameters Removed — 400 Error from temperature / top_p / top_k
- Breaking Point 2/3: Extended Thinking Budget Removed — 400 Error if budget_tokens Remains
- Breaking Point 3/3: Assistant Message Prefill Removed — Merged into 400 Error (See Below)
- Additional Note 1: Thinking Content Omitted by Default — Silent Change, Watch for UX Degradation
- Additional Note 2: Tokenizer Change — Up to 1.35× Token Consumption for the Same Text
- Breaking Point 3/3 Details: Assistant Message Prefill Removed — 400 Error, Use Structured Output or System Prompts
- Code Diff Examples — Understand 5 Lines to Rewrite via Before / After
- Python SDK — Remove temperature / top_p / budget_tokens → Adaptive + effort
- TypeScript SDK — Same 5-Line Rewrite as Python (Use as any to Work Around Unrecognized Fields)
- Operational Notes — Opus 4.6 Retirement Unannounced, Pricing Unchanged, Token Measurement Required
- Opus 4.6 End-of-Support Notice — Retirement Schedule Not Announced (as of 2026-04)
- Cost Comparison — 4.6 and 4.7 Have Identical Unit Pricing ($5/$25 per MTok), Token Consumption Up to 35% Higher
- When to Use the xhigh Effort Level — Officially Recommended to Start with xhigh for Coding and Agent Use Cases
- Migration Checklist (Save This) — 6 Required Items + 8 Recommended Items + Validation
- 6 Required Items — Model ID / temperature / top_p / top_k / budget_tokens / prefill
- 8 Recommended Items — Increase max_tokens / Restore display / Estimate Image Costs / Evaluate xhigh / etc.
- Validation — Benchmark Representative Workloads and Always Measure Before Going to Production
- Sources (Primary Information)
3 Places Where You Get Stuck from 4.6 (Guaranteed 400 Errors) + 2 Additional Notes
All 3 guaranteed breaking points in Opus 4.6 → 4.7 are breaking changes that return HTTP 400. The remaining 2 (tokenizer change and Thinking omission) are silent changes that cause quality degradation or cost increases source.
Breaking Point 1/3: Sampling Parameters Removed — 400 Error from temperature / top_p / top_k
Setting temperature, top_p, or top_k to any non-default value will return
HTTP 400
source.
How to fix: Remove these parameters entirely from your request payload.
To control output behavior, use system prompts as an alternative.
Note that temperature = 0 has never guaranteed identical output.
How to find affected code:
# Example: find affected locations in your codebase
grep -rn "temperature\|top_p\|top_k" ./src/
Breaking Point 2/3: Extended Thinking Budget Removed — 400 Error if budget_tokens Remains
Specifying thinking: {"type": "enabled", "budget_tokens": N} will return
HTTP 400
source.
Adaptive Thinking is the only supported thinking mode in Opus 4.7.
Adaptive Thinking is off by default. If you want to use the thinking feature, explicitly set thinking: {type: "adaptive"}.
# Before (Opus 4.6)
thinking = {"type": "enabled", "budget_tokens": 32000}
# After (Opus 4.7)
thinking = {"type": "adaptive"}
output_config = {"effort": "high"}
Breaking Point 3/3: Assistant Message Prefill Removed — Merged into 400 Error (See Below)
The third breaking point is the removal of assistant message prefill. Details are in [Additional Note 1] in this section. The alternative is structured output or system prompts source.
Additional Note 1: Thinking Content Omitted by Default — Silent Change, Watch for UX Degradation
In Opus 4.7, thinking content is omitted by default (the default for display has changed to "omitted").
No error is thrown, but products that stream reasoning output may experience
long silent gaps before text begins
source.
If you want to show reasoning to users, explicitly set display: "summarized":
thinking = {
"type": "adaptive",
"display": "summarized", # defaults to "omitted" if not set
}
Additional Note 2: Tokenizer Change — Up to 1.35× Token Consumption for the Same Text
Opus 4.7 uses a new tokenizer, which may consume up to approximately 35% more tokens for the same input text compared to Opus 4.6 (ranging from 1.0× to 1.35× depending on content type) source.
- It is recommended to update
max_tokensto a value with more headroom. - For workloads including image processing: token consumption per image may also increase up to approximately 3× due to high-resolution support.
- Measure actual consumption with the
/v1/messages/count_tokensendpoint.
Breaking Point 3/3 Details: Assistant Message Prefill Removed — 400 Error, Use Structured Output or System Prompts
As a cumulative change from Opus 4.6, assistant message prefill now returns a 400 error. Use structured output (Structured Outputs) or system prompts as alternatives source.
Code Diff Examples — Understand 5 Lines to Rewrite via Before / After
Python SDK — Remove temperature / top_p / budget_tokens → Adaptive + effort
Key points for this section:
import anthropic
client = anthropic.Anthropic()
# =====================================================
# Before: Opus 4.6
# =====================================================
response = client.messages.create(
model="claude-opus-4-6",
max_tokens=64000,
temperature=0.7, # deprecated → remove
top_p=0.9, # deprecated → remove
thinking={
"type": "enabled",
"budget_tokens": 32000 # deprecated → change to Adaptive Thinking
},
messages=[{"role": "user", "content": "Please review this code."}],
)
# =====================================================
# After: Opus 4.7
# =====================================================
response = client.messages.create(
model="claude-opus-4-7", # update model ID
max_tokens=64000,
# temperature / top_p / top_k are removed
thinking={"type": "adaptive"}, # Adaptive Thinking
output_config={"effort": "high"}, # specify effort level
messages=[{"role": "user", "content": "Please review this code."}],
)
If you want to show thinking content to users:
# When displaying Thinking content to users
response = client.messages.create(
model="claude-opus-4-7",
max_tokens=64000,
thinking={
"type": "adaptive",
"display": "summarized", # explicitly enable
},
output_config={"effort": "high"},
messages=[{"role": "user", "content": "Please solve a problem requiring complex reasoning."}],
)
TypeScript SDK — Same 5-Line Rewrite as Python (Use as any to Work Around Unrecognized Fields)
Key points for this section:
import Anthropic from "@anthropic-ai/sdk";
const client = new Anthropic();
// =====================================================
// Before: Opus 4.6
// =====================================================
const responseBefore = await client.messages.create({
model: "claude-opus-4-6",
max_tokens: 64000,
temperature: 0.7, // deprecated → remove
top_p: 0.9, // deprecated → remove
thinking: {
type: "enabled",
budget_tokens: 32000, // deprecated → change to Adaptive Thinking
},
messages: [{ role: "user", content: "Please review this code." }],
} as any);
// =====================================================
// After: Opus 4.7
// =====================================================
const responseAfter = await client.messages.create({
model: "claude-opus-4-7", // update model ID
max_tokens: 64000,
// temperature / top_p / top_k are removed
thinking: { type: "adaptive" }, // Adaptive Thinking
output_config: { effort: "high" }, // specify effort level
messages: [{ role: "user", content: "Please review this code." }],
} as any);
Operational Notes — Opus 4.6 Retirement Unannounced, Pricing Unchanged, Token Measurement Required
Opus 4.6 End-of-Support Notice — Retirement Schedule Not Announced (as of 2026-04)
As of now, Anthropic has not announced a retirement schedule for Opus 4.6. Check the Anthropic model deprecations page for official deprecation information.
For reference: Claude Sonnet 4 and Claude Opus 4 (both 20250514 snapshots) are scheduled for retirement on
June 15, 2026
source.
Cost Comparison — 4.6 and 4.7 Have Identical Unit Pricing ($5/$25 per MTok), Token Consumption Up to 35% Higher
Key points for this section:
| Category | Unit Price (excl. tax, USD) |
|---|---|
| Input tokens | $5.00 / 1M tokens |
| Output tokens | $25.00 / 1M tokens |
There is no price change from Opus 4.6 source. For the latest and most accurate pricing, see source.
Note: Due to the tokenizer change, token consumption may increase even for the same input (up to 35% more). It is recommended to measure actual costs against representative workloads before moving to production.
When to Use the xhigh Effort Level — Officially Recommended to Start with xhigh for Coding and Agent Use Cases
The xhigh effort level newly added in Opus 4.7 is the optimal setting for coding and agent use cases
source.
| Effort Level | Recommended Use Case |
|---|---|
max |
Tasks requiring maximum accuracy. May over-think — test carefully |
xhigh |
Recommended for coding and agent use cases (new in Opus 4.7) |
high |
Default. Appropriate for most knowledge-intensive tasks |
medium |
Cost-conscious workloads where slightly lower accuracy is acceptable |
low |
Short, clearly scoped, or latency-sensitive tasks |
Source: source When using xhigh or max, it is recommended to set max_tokens to
at least 64,000 tokens
source.
The specific token consumption multiplier when using xhigh varies by workload and task complexity. Measure with your actual workload before going to production.
Migration Checklist (Save This) — 6 Required Items + 8 Recommended Items + Validation
Copy and use as needed.
6 Required Items — Model ID / temperature / top_p / top_k / budget_tokens / prefill
Key points for this section:
- Change model ID from
claude-opus-4-6→claude-opus-4-7 - Remove
temperaturefrom the request - Remove
top_pfrom the request - Remove
top_kfrom the request - Remove
thinking: {type: "enabled", budget_tokens: N}
→ Replace with: thinking: {type: "adaptive"} + output_config: {effort: "high"}
- Remove assistant message prefill
→ Replace with: structured output or system prompts
8 Recommended Items — Increase max_tokens / Restore display / Estimate Image Costs / Evaluate xhigh / etc.
Key points for this section:
- Update
max_tokensto a value with more headroom (for tokenizer change) - Where reasoning content is displayed: add
thinking.display = "summarized" - Workloads handling images: update cost estimates for high-resolution support (up to ~3×)
- Coding and agent use cases: evaluate with
effortset to"xhigh" - Agent loops: consider adopting Task Budgets (beta)
- Client-side token estimation code: re-measure and recalibrate for Opus 4.7
- Coordinate conversion code: remove scale factor conversion (now 1:1 pixel mapping)
- Cybersecurity-related tasks: apply to the Cyber Verification Program
Validation — Benchmark Representative Workloads and Always Measure Before Going to Production
Key points for this section:
- Re-measure end-to-end cost and latency
- Re-evaluate output style (tone, length, and reaction patterns)
- Verify tool call frequency in agent workflows
- Check the format of progress messages in long-running agents
Sources (Primary Information)
- source — Details on new features and breaking changes
- source — Official migration guide (includes checklist)
- source — Adaptive Thinking API spec and code examples
- source — Effort level configuration
- source — Model list and pricing (referenced: 2026-04-23)
- source — Model retirement schedule
- Anthropic: Pricing — Latest pricing (referenced: 2026-04-23)