Feature Request: Configurable Context Compaction Threshold

[WietRob]

OpenCode Feature Request: Configurable Context Compaction Threshold

Submitted by: @roberto_schmidt
Date: 2026-01-30
Priority: High
Category: Core Functionality / Configuration

---

Summary

Currently, OpenCode triggers context compaction at a hardcoded 75% threshold of a model's context window. This causes severe performance degradation for long-context models (Gemini, Claude, GPT-4) before compaction occurs, as these models begin losing coherence well before the 75% mark.

Request: Expose the compaction threshold as a user-configurable setting in opencode.json.

---

Problem Statement

Current Behavior

• Compaction triggers at exactly 75% of the model's advertised context window
• This is hardcoded in the OpenCode binary and cannot be changed
• Example: Gemini with 1M context triggers compaction at 786k tokens

Impact

• Gemini models: Performance degradation starts at ~30% (300k tokens), but compaction doesn't trigger until 75% (786k)
• Claude models: Quality drops significantly after ~50% of context
• Result: Users experience 2-3x slower responses, hallucinations, and poor code quality before automatic compaction kicks in

---

Proposed Solution

Add a compaction configuration section to opencode.json:

{
  "$schema": "https://opencode.ai/config.json",
  "compaction": {
    "threshold": 0.40,
    "strategy": "summarize",
    "preserveRecentMessages": 10,
    "preserveSystemPrompt": true
  },
  "provider": {
    ...
  }
}

Configuration Options

Option	Type	Default	Description
threshold	number (0.0-1.0)	0.75	Percentage of context window at which to trigger compaction
strategy	string	"summarize"	Compaction strategy: "summarize", "truncate", "archive"
preserveRecentMessages	number	10	Number of recent messages to always preserve
preserveSystemPrompt	boolean	true	Always preserve the system prompt

Per-Model Overrides

Allow model-specific thresholds:

{
  "provider": {
    "google": {
      "models": {
        "gemini-1.5-pro": {
          "limit": { "context": 1048576 },
          "compaction": {
            "threshold": 0.30
          }
        }
      }
    }
  }
}

---

Use Cases

1. VRP Optimization Work (CuraOps): Need compaction at 30% for Gemini to maintain constraint tracking accuracy
2. Long Document Analysis: Users working with 500k+ token documents need early compaction to preserve coherence
3. Multi-Session Coding: 8+ hour coding sessions accumulate context that degrades model performance

---

Alternative Solutions Considered

1. Manual compaction: Users can trigger session.compact manually, but this interrupts workflow and requires constant monitoring
2. Smaller context windows: Setting limit.context to lower values doesn't work - OpenCode uses the model's ACTUAL window, not the config value
3. Different models: Switching to shorter-context models sacrifices capability

---

Implementation Notes

The compaction logic already exists in the OpenCode binary. This feature request is about exposing the hardcoded 0.75 value as a configuration parameter.

Relevant SDK types found:

compaction?: {
  auto?: boolean;     // Already exists
  prune?: boolean;    // Already exists
  threshold?: number; // REQUESTED: 0.0-1.0
}

---

Benefits

1. Improved productivity: Models stay in high-performance zone longer
2. Better code quality: Less context degradation = fewer bugs
3. User control: Power users can tune for their specific workflows
4. Backward compatible: Default remains 0.75, no breaking changes

---

Related Issues

• Context window management for long-running sessions
• Performance degradation in multi-step workflows
• Memory/Neo4j integration for persistent context

---

Contact: roberto.schmidt@curaops.de
Willing to test: Yes, happy to validate beta implementations

[github-actions]

This issue might be a duplicate of existing issues. Please check:

• GPT 5.2 Codex - Compaction happens way too early and context limit is wrong #11086: GPT 5.2 Codex - Compaction happens way too early and context limit is wrong
• [FEATURE]: Support Model-Level Configuration override Provider-Level, such as baseURL and apiKey #11287: [FEATURE]: Support Model-Level Configuration override Provider-Level, such as baseURL and apiKey
• [FEATURE]: Configurable per-session token budget limit #11138: [FEATURE]: Configurable per-session token budget limit (closed)

The core request aligns with #11086 regarding early compaction triggering at hardcoded thresholds. Additionally, #11287 addresses the broader feature of model-level configuration overrides that could support per-model compaction thresholds.

Feel free to ignore if your specific compaction threshold configuration needs differ from these issues.

[jeremyakers]

The "auto-archive" mode is exactly what I want/need. Being able to archive old (timestamped) messages into a location on disk where the agent can still access them is best of both worlds: If the agent ever needs to "refer back" to something that exceeds it's context: It can just do a surgical ripgrep / grepai / aigrep search using a combination of timestamp filter plus contextual search of that archive to reference that archived information.

[iyunbo]

➕
The best practices proposed by Anthropic is mostly about "context window management":

Most best practices are based on one constraint: Claude’s context window fills up fast, and performance degrades as it fills.

The same principles apply to most of LLM coding tools including opencode, therefore, this feature is a high priority IMO. 🙏

[iyunbo]

#10123 seems the PR to address it.

[jeremyakers]

#10123 seems the PR to address it.

That PR doesn't seem to add auto archive. But I created a plugin that addresses that use case:

https://github.com/jeremyakers/opencode-plugins/tree/main/packages/opencode-archive-before-compaction

I also published to npm so you can add it with:

opencode.json:

{
  "plugin": ["opencode-archive-before-compaction"]
}

[WietRob]

Thanks for the reference to related issues!

I'd like to clarify how this request differs:

• GPT 5.2 Codex - Compaction happens way too early and context limit is wrong #11086 is about compaction happening too early
• [FEATURE]: Support Model-Level Configuration override Provider-Level, such as baseURL and apiKey #11287 is about model-level config overrides (general)
• [FEATURE]: Configurable per-session token budget limit #11138 is about session token budgets (global limits)

This issue is specifically about:

• Per-model compaction threshold configuration
• Problem: Models like Gemini lose quality at ~30% context (300k tokens)
• Current hardcoded 75% threshold means models work in degraded state for ~600k tokens
• Need ability to set compaction.threshold: 0.30 per-model

The model-level config (#11287) could support this, but we need to expose the specific threshold parameter first.

[WietRob]

@jeremyakers Thanks for the validation! The 'auto-archive' mode with timestamp-based archiving and searchable context is exactly the direction we need.

Could the compaction threshold be exposed as a model-level configuration option alongside the auto-archive feature? That would give users both:

1. Fine-grained control over when compaction triggers (per-model thresholds)
2. Persistent access to archived context for surgical retrieval

This seems complementary to your 'best of both worlds' approach.

[WietRob]

@saksham1341 Wow, thank you for the quick implementation! 🙌

I'd be happy to test this out. Could you provide guidance on:

1. How to update my configuration - what's the new JSON schema for per-model thresholds?
2. How to test - should I restart OpenCode? Any commands to verify it's working?
3. What to test specifically - I'll verify it compacts at the new threshold vs the old 75%

Looking forward to testing this! This will be huge for CuraOps VRP optimization with long-context models.

cc: @jeremyakers (FYI - this feature is now implemented!)

[WietRob]

@saksham1341 Thanks for the detailed example! I've updated my configuration:

{
  "compaction": {
    "token_threshold": 300000,
    "context_threshold": 0.30,
    "models": {
      "google/antigravity-gemini-3-flash": {
        "token_threshold": 300000,
        "context_threshold": 0.30
      },
      "google/antigravity-gemini-3-pro-high": {
        "token_threshold": 300000,
        "context_threshold": 0.30
      },
      "google/antigravity-gemini-3-pro-low": {
        "token_threshold": 300000,
        "context_threshold": 0.30
      }
    }
  }
}

I'm ready to test. How should I verify it's working?

• Just monitor when compaction happens?
• Use a session.log or debug flag?
• Should I restart OpenCode after changing config?

Looking forward to testing this!

[WietRob]

@saksham1341 Also added GLM-4.7 to my config:

"opencode/glm-4.7-free": {
  "token_threshold": 138000,
  "context_threshold": 0.50
}

This compacts at 138k tokens (~50% of the model's likely context window of 128k+). Perfect for coding sessions with GLM.