fix(bedrock_mantle): correct grok-4.3 and gemma-4 token limits

Four bedrock_mantle entries advertise token limits that do not match what
the service enforces. Verified by probing the live endpoint
(bedrock-mantle us-east-2) and reading the caps it reports back:

  model                  field  current    actual
  xai.grok-4.3           input   131072   1048576
  xai.grok-4.3          output    16384   1048576
  google.gemma-4-31b        in   256000    262144
  google.gemma-4-26b-a4b    in   256000    262144
  google.gemma-4-e2b        in   128000    131072

grok-4.3 is the significant one: the input limit is understated 8x. As
with the GPT-5.6 entries, the non-Bedrock counterpart already carries the
larger value (xai/grok-4.3 reads 1000000), which is what suggested the
bedrock_mantle numbers were stale rather than deliberate.

Evidence, input:
  "prompt tokens (1300031) exceed customer model maximum (1048576)"
and a real request with 394937 prompt tokens (3x the advertised max)
completed successfully on xai.grok-4.3, correctly retrieving a fact
planted at 85% depth.

Evidence, output:
  max_tokens=1048576 accepted; 1048577 -> "'max_tokens' (1048577) exceeds
  model maximum (1048576)"
The gemma-4 models behave the same way, so their max_output_tokens and
max_tokens move with the input value (they were already equal).

The understated values cause premature context-window errors and early
auto-compaction, and clamp max_tokens far below what the model allows.

Left alone deliberately: openai.gpt-oss-* keep 131072 (they are not
served on the Responses or /openai/v1 chat routes, so the cap could not
be probed the same way) and the openai.gpt-5.x entries, which are handled
separately.

litellm/model_prices_and_context_window_backup.json

@@ -45394,9 +45394,9 @@
         "input_cost_per_token": 1.4e-07,
         "output_cost_per_token": 4e-07,
         "litellm_provider": "bedrock_mantle",
-        "max_input_tokens": 256000,
-        "max_output_tokens": 256000,
-        "max_tokens": 256000,
+        "max_input_tokens": 262144,
+        "max_output_tokens": 262144,
+        "max_tokens": 262144,
         "mode": "chat",
         "use_openai_responses_path": true,
         "supported_endpoints": [
@@ -45413,9 +45413,9 @@
         "input_cost_per_token": 1.3e-07,
         "output_cost_per_token": 4e-07,
         "litellm_provider": "bedrock_mantle",
-        "max_input_tokens": 256000,
-        "max_output_tokens": 256000,
-        "max_tokens": 256000,
+        "max_input_tokens": 262144,
+        "max_output_tokens": 262144,
+        "max_tokens": 262144,
         "mode": "chat",
         "use_openai_responses_path": true,
         "supported_endpoints": [
@@ -45432,9 +45432,9 @@
         "input_cost_per_token": 4e-08,
         "output_cost_per_token": 8e-08,
         "litellm_provider": "bedrock_mantle",
-        "max_input_tokens": 128000,
-        "max_output_tokens": 128000,
-        "max_tokens": 128000,
+        "max_input_tokens": 131072,
+        "max_output_tokens": 131072,
+        "max_tokens": 131072,
         "mode": "chat",
         "use_openai_responses_path": true,
         "supported_endpoints": [
@@ -45453,9 +45453,9 @@
         "output_cost_per_token": 2.5e-06,
         "cache_read_input_token_cost": 2e-07,
         "litellm_provider": "bedrock_mantle",
-        "max_input_tokens": 131072,
-        "max_output_tokens": 16384,
-        "max_tokens": 16384,
+        "max_input_tokens": 1048576,
+        "max_output_tokens": 1048576,
+        "max_tokens": 1048576,
         "mode": "chat",
         "supported_endpoints": [
             "/v1/chat/completions",

model_prices_and_context_window.json

@@ -45515,9 +45515,9 @@
         "input_cost_per_token": 1.4e-07,
         "output_cost_per_token": 4e-07,
         "litellm_provider": "bedrock_mantle",
-        "max_input_tokens": 256000,
-        "max_output_tokens": 256000,
-        "max_tokens": 256000,
+        "max_input_tokens": 262144,
+        "max_output_tokens": 262144,
+        "max_tokens": 262144,
         "mode": "chat",
         "use_openai_responses_path": true,
         "supported_endpoints": [
@@ -45534,9 +45534,9 @@
         "input_cost_per_token": 1.3e-07,
         "output_cost_per_token": 4e-07,
         "litellm_provider": "bedrock_mantle",
-        "max_input_tokens": 256000,
-        "max_output_tokens": 256000,
-        "max_tokens": 256000,
+        "max_input_tokens": 262144,
+        "max_output_tokens": 262144,
+        "max_tokens": 262144,
         "mode": "chat",
         "use_openai_responses_path": true,
         "supported_endpoints": [
@@ -45553,9 +45553,9 @@
         "input_cost_per_token": 4e-08,
         "output_cost_per_token": 8e-08,
         "litellm_provider": "bedrock_mantle",
-        "max_input_tokens": 128000,
-        "max_output_tokens": 128000,
-        "max_tokens": 128000,
+        "max_input_tokens": 131072,
+        "max_output_tokens": 131072,
+        "max_tokens": 131072,
         "mode": "chat",
         "use_openai_responses_path": true,
         "supported_endpoints": [
@@ -45574,9 +45574,9 @@
         "output_cost_per_token": 2.5e-06,
         "cache_read_input_token_cost": 2e-07,
         "litellm_provider": "bedrock_mantle",
-        "max_input_tokens": 131072,
-        "max_output_tokens": 16384,
-        "max_tokens": 16384,
+        "max_input_tokens": 1048576,
+        "max_output_tokens": 1048576,
+        "max_tokens": 1048576,
         "mode": "chat",
         "supported_endpoints": [
             "/v1/chat/completions",

tests/test_litellm/llms/bedrock_mantle/test_bedrock_mantle_transformation.py

@@ -641,9 +641,9 @@ class TestBedrockMantlePricing:
 @pytest.mark.parametrize(
     "model_id,input_cost,output_cost,max_tokens",
     [
-        ("google.gemma-4-31b", 1.4e-07, 4e-07, 256000),
-        ("google.gemma-4-26b-a4b", 1.3e-07, 4e-07, 256000),
-        ("google.gemma-4-e2b", 4e-08, 8e-08, 128000),
+        ("google.gemma-4-31b", 1.4e-07, 4e-07, 262144),
+        ("google.gemma-4-26b-a4b", 1.3e-07, 4e-07, 262144),
+        ("google.gemma-4-e2b", 4e-08, 8e-08, 131072),
     ],
 )
 def test_gemma_4_bedrock_mantle_model_metadata(
@@ -685,3 +685,20 @@ def test_gemma_4_models_register_under_bedrock_mantle(local_cost_map, model_id):
     resolved_model, provider, _, _ = litellm.get_llm_provider(full_model_name)
     assert provider == "bedrock_mantle"
     assert resolved_model == model_id
+
+
+@pytest.mark.parametrize(
+    "model_id, expected_tokens",
+    [
+        ("xai.grok-4.3", 1048576),
+        ("google.gemma-4-31b", 262144),
+        ("google.gemma-4-26b-a4b", 262144),
+        ("google.gemma-4-e2b", 131072),
+    ],
+)
+def test_context_windows_match_bedrock_limits(
+    local_cost_map, model_id, expected_tokens
+):
+    info = litellm.get_model_info(model=model_id, custom_llm_provider="bedrock_mantle")
+    assert info["max_input_tokens"] == expected_tokens
+    assert info["max_output_tokens"] == expected_tokens