diff --git a/examples/geo3k_vlm_multi_turn/rollout.py b/examples/geo3k_vlm_multi_turn/rollout.py
index 2bb1bef2fc..04eb97d9b1 100644
--- a/examples/geo3k_vlm_multi_turn/rollout.py
+++ b/examples/geo3k_vlm_multi_turn/rollout.py
@@ -167,6 +167,24 @@ def _prepare_initial_inputs(sample: Sample, processor, tokenizer):
     return prompt_ids, image_data, sample.multimodal_train_inputs
 
 
+def _remaining_generation_budget(
+    sample: Sample, response_tokens: list[int], args: Any, sampling_params: dict
+) -> int | None:
+    # SGLang max_new_tokens is a response-side budget; prompt tokens are already
+    # part of the request and should only count against the optional context cap.
+    budgets = []
+
+    context_len = getattr(args, "rollout_max_context_len", None)
+    if context_len is not None:
+        budgets.append(int(context_len) - len(sample.tokens))
+
+    max_new_tokens = sampling_params.get("max_new_tokens")
+    if max_new_tokens is not None:
+        budgets.append(int(max_new_tokens) - len(response_tokens))
+
+    return min(budgets) if budgets else None
+
+
 def _prepare_start_state(sample: Sample, state, args: Any, sampling_params: dict):
     prompt_ids, image_data, init_mm_train = _prepare_initial_inputs(sample, state.processor, state.tokenizer)
     current_image_data = image_data
@@ -181,11 +199,7 @@ def _prepare_start_state(sample: Sample, state, args: Any, sampling_params: dict
     sample.rollout_log_probs = sample.rollout_log_probs or []
     sample.response_length = len(response_tokens)
 
-    budget = None
-    if args.rollout_max_context_len is not None:
-        budget = args.rollout_max_context_len - len(sample.tokens)
-    elif sampling_params.get("max_new_tokens") is not None:
-        budget = sampling_params["max_new_tokens"] - len(sample.tokens)
+    budget = _remaining_generation_budget(sample, response_tokens, args, sampling_params)
     return current_image_data, response_tokens, budget, multimodal_train_inputs_buffer
 
 
diff --git a/tests/test_geo3k_vlm_multi_turn_budget.py b/tests/test_geo3k_vlm_multi_turn_budget.py
new file mode 100644
index 0000000000..0985145916
--- /dev/null
+++ b/tests/test_geo3k_vlm_multi_turn_budget.py
@@ -0,0 +1,117 @@
+from __future__ import annotations
+
+import importlib
+import sys
+import types
+from argparse import Namespace
+from pathlib import Path
+from types import SimpleNamespace
+
+import pytest
+
+REPO_ROOT = Path(__file__).resolve().parents[1]
+if str(REPO_ROOT) not in sys.path:
+    sys.path.insert(0, str(REPO_ROOT))
+
+MODULE_NAME = "examples.geo3k_vlm_multi_turn.rollout"
+pytestmark = pytest.mark.unit
+
+
+class _FakeTokenizer:
+    bos_token_id = None
+
+    def encode(self, text, add_special_tokens=False):
+        del add_special_tokens
+        return [100 + idx for idx, _ in enumerate(str(text).split())]
+
+
+class _FakeSample(SimpleNamespace):
+    def __init__(self, *, prompt="a b c", tokens=None, loss_mask=None, rollout_log_probs=None):
+        super().__init__(
+            prompt=prompt,
+            tokens=list(tokens or []),
+            multimodal_inputs=None,
+            multimodal_train_inputs=None,
+            loss_mask=loss_mask,
+            rollout_log_probs=rollout_log_probs,
+            response_length=0,
+        )
+
+
+@pytest.fixture()
+def rollout(monkeypatch):
+    fake_torch = types.ModuleType("torch")
+    fake_torch.Tensor = object
+    fake_torch.cat = lambda values, dim=0: list(values)
+    monkeypatch.setitem(sys.modules, "torch", fake_torch)
+
+    fake_sglang_rollout = types.ModuleType("slime.rollout.sglang_rollout")
+    fake_sglang_rollout.GenerateState = object
+    monkeypatch.setitem(sys.modules, "slime.rollout.sglang_rollout", fake_sglang_rollout)
+
+    fake_http = types.ModuleType("slime.utils.http_utils")
+    fake_http.post = None
+    monkeypatch.setitem(sys.modules, "slime.utils.http_utils", fake_http)
+
+    fake_processing = types.ModuleType("slime.utils.processing_utils")
+    fake_processing.encode_image_for_rollout_engine = lambda image: image
+    monkeypatch.setitem(sys.modules, "slime.utils.processing_utils", fake_processing)
+
+    fake_types = types.ModuleType("slime.utils.types")
+    fake_types.Sample = object
+    monkeypatch.setitem(sys.modules, "slime.utils.types", fake_types)
+
+    sys.modules.pop(MODULE_NAME, None)
+    try:
+        yield importlib.import_module(MODULE_NAME)
+    finally:
+        sys.modules.pop(MODULE_NAME, None)
+
+
+def _start_state(rollout, sample, *, context_len=None, max_new_tokens=5):
+    state = SimpleNamespace(processor=None, tokenizer=_FakeTokenizer())
+    return rollout._prepare_start_state(
+        sample,
+        state,
+        Namespace(rollout_max_context_len=context_len),
+        {"max_new_tokens": max_new_tokens},
+    )
+
+
+def test_geo3k_multi_turn_response_budget_does_not_charge_prompt_tokens(rollout):
+    sample = _FakeSample(prompt="a b c")
+
+    _image_data, response_tokens, budget, _mm_buffer = _start_state(rollout, sample)
+
+    assert response_tokens == []
+    assert sample.tokens == [100, 101, 102]
+    assert budget == 5
+
+
+def test_geo3k_multi_turn_response_budget_counts_existing_response_only(rollout):
+    sample = _FakeSample(
+        prompt="a b c",
+        tokens=[100, 101, 102, 201, 202],
+        loss_mask=[1, 1],
+        rollout_log_probs=[-0.1, -0.2],
+    )
+
+    _image_data, response_tokens, budget, _mm_buffer = _start_state(rollout, sample)
+
+    assert response_tokens == [201, 202]
+    assert sample.response_length == 2
+    assert budget == 3
+
+
+def test_geo3k_multi_turn_budget_respects_context_and_response_limits(rollout):
+    sample = _FakeSample(
+        prompt="a b c",
+        tokens=[100, 101, 102, 201, 202, 203, 204],
+        loss_mask=[1, 1, 1, 1],
+        rollout_log_probs=[-0.1, -0.2, -0.3, -0.4],
+    )
+
+    _image_data, response_tokens, budget, _mm_buffer = _start_state(rollout, sample, context_len=10)
+
+    assert response_tokens == [201, 202, 203, 204]
+    assert budget == 1