fix(e2e): use stable MiniMax model default

.gitea/workflows/continuous-synth-e2e.yml

@@ -118,7 +118,7 @@ jobs:
     timeout-minutes: 20
     env:
       # claude-code default: cold-start ~5 min (comparable to langgraph),
-      # but uses MiniMax-M2.7-highspeed via the template's third-party-
+      # but uses MiniMax-M2 via the template's third-party-
       # Anthropic-compat path (workspace-configs-templates/claude-code-
       # default/config.yaml:64-69). MiniMax is ~5-10x cheaper than
       # gpt-4.1-mini per token AND avoids the recurring OpenAI quota-
@@ -131,9 +131,9 @@ jobs:
       # on the per-runtime default ("sonnet" → routes to direct
       # Anthropic, defeats the cost saving). Operators can override
       # via workflow_dispatch by setting a different E2E_MODEL_SLUG
-      # input if they need to exercise a specific model. M2.7-highspeed
-      # is "Token Plan only" but cheap-per-token and fast.
-      E2E_MODEL_SLUG: ${{ github.event.inputs.model_slug || 'MiniMax-M2.7-highspeed' }}
+      # input if they need to exercise a specific model. MiniMax-M2 is the
+      # stable staging MiniMax path used by the full-SaaS smoke.
+      E2E_MODEL_SLUG: ${{ github.event.inputs.model_slug || 'MiniMax-M2' }}
       # Bound to 10 min so a stuck provision fails the run instead of
       # holding up the next cron firing. 15-min default in the script
       # is for the on-PR full lifecycle where we have more headroom.

.gitea/workflows/e2e-staging-saas.yml

@@ -161,7 +161,7 @@ jobs:
       # and defeats the cost saving. Operators can override via the
       # workflow_dispatch flow (no input wired here yet — runtime
       # override is enough for ad-hoc).
-      E2E_MODEL_SLUG: ${{ github.event.inputs.runtime == 'hermes' && 'openai/gpt-4o' || github.event.inputs.runtime == 'langgraph' && 'openai:gpt-4o' || 'MiniMax-M2.7-highspeed' }}
+      E2E_MODEL_SLUG: ${{ github.event.inputs.runtime == 'hermes' && 'openai/gpt-4o' || github.event.inputs.runtime == 'langgraph' && 'openai:gpt-4o' || 'MiniMax-M2' }}
       E2E_RUN_ID: "${{ github.run_id }}-${{ github.run_attempt }}"
       E2E_KEEP_ORG: ${{ github.event.inputs.keep_org && '1' || '0' }}
 

.gitea/workflows/staging-smoke.yml

@@ -112,9 +112,9 @@ jobs:
       E2E_RUNTIME: claude-code
       # Pin the smoke to a specific MiniMax model rather than relying
       # on the per-runtime default (which could resolve to "sonnet" →
-      # direct Anthropic and defeat the cost saving). M2.7-highspeed
-      # is "Token Plan only" but cheap-per-token and fast.
-      E2E_MODEL_SLUG: MiniMax-M2.7-highspeed
+      # direct Anthropic and defeat the cost saving). MiniMax-M2 is the
+      # stable staging MiniMax path used by the full-SaaS smoke.
+      E2E_MODEL_SLUG: MiniMax-M2
       E2E_RUN_ID: "smoke-${{ github.run_id }}"
       # Debug-only: when an operator dispatches with keep_on_failure=true,
       # the smoke script's E2E_KEEP_ORG=1 path skips teardown so the

tests/test_e2e_minimax_defaults.py

@@ -0,0 +1,18 @@
+from pathlib import Path
+
+
+ROOT = Path(__file__).resolve().parents[1]
+
+
+def test_staging_e2e_workflows_use_stable_minimax_default() -> None:
+    """Keep cron/push E2E on the same MiniMax model as the smoke-tested script."""
+    workflow_paths = [
+        ".gitea/workflows/e2e-staging-saas.yml",
+        ".gitea/workflows/staging-smoke.yml",
+        ".gitea/workflows/continuous-synth-e2e.yml",
+    ]
+
+    for rel in workflow_paths:
+        text = (ROOT / rel).read_text()
+        assert "MiniMax-M2.7-highspeed" not in text
+        assert "MiniMax-M2" in text