[Mistral-Small 3.1] Update docs and tests (#14977)

Signed-off-by: Roger Wang <ywang@roblox.com>
Co-authored-by: Roger Wang <ywang@roblox.com>

docs/source/models/supported_models.md

@@ -879,7 +879,7 @@ See [this page](#generative-models) for more information on how to use generativ
 - * `PixtralForConditionalGeneration`
   * Pixtral
   * T + I<sup>+</sup>
-  * `mistralai/Pixtral-12B-2409`, `mistral-community/pixtral-12b`, etc.
+  * `mistralai/Mistral-Small-3.1-24B-Instruct-2503`, `mistral-community/pixtral-12b`, etc.
   *
   * ✅︎
   * ✅︎

examples/offline_inference/pixtral.py

@@ -6,14 +6,14 @@ import argparse
 from vllm import LLM
 from vllm.sampling_params import SamplingParams
 
-# This script is an offline demo for running Pixtral.
+# This script is an offline demo for running Mistral-Small-3
 #
 # If you want to run a server/client setup, please follow this code:
 #
 # - Server:
 #
 # ```bash
-# vllm serve mistralai/Pixtral-12B-2409 --tokenizer-mode mistral --limit-mm-per-prompt 'image=4' --max-model-len 16384
+# vllm serve mistralai/Mistral-Small-3.1-24B-Instruct-2503 --tokenizer-mode mistral --limit-mm-per-prompt 'image=4' --max-model-len 16384
 # ```
 #
 # - Client:
@@ -23,7 +23,7 @@ from vllm.sampling_params import SamplingParams
 # --header 'Content-Type: application/json' \
 # --header 'Authorization: Bearer token' \
 # --data '{
-#     "model": "mistralai/Pixtral-12B-2409",
+#     "model": "mistralai/Mistral-Small-3.1-24B-Instruct-2503",
 #     "messages": [
 #       {
 #         "role": "user",
@@ -44,7 +44,7 @@ from vllm.sampling_params import SamplingParams
 
 
 def run_simple_demo(args: argparse.Namespace):
-    model_name = "mistralai/Pixtral-12B-2409"
+    model_name = "mistralai/Mistral-Small-3.1-24B-Instruct-2503"
     sampling_params = SamplingParams(max_tokens=8192)
 
     # Lower max_model_len and/or max_num_seqs on low-VRAM GPUs.
@@ -83,7 +83,7 @@ def run_simple_demo(args: argparse.Namespace):
 
 
 def run_advanced_demo(args: argparse.Namespace):
-    model_name = "mistralai/Pixtral-12B-2409"
+    model_name = "mistralai/Mistral-Small-3.1-24B-Instruct-2503"
     max_img_per_msg = 5
     max_tokens_per_img = 4096
 

tests/models/decoder_only/vision_language/test_pixtral.py

@@ -4,7 +4,6 @@
 Run `pytest tests/models/test_mistral.py`.
 """
 import json
-import uuid
 from dataclasses import asdict
 from typing import TYPE_CHECKING, Any, Optional
 
@@ -16,8 +15,7 @@ from mistral_common.tokens.tokenizers.mistral import MistralTokenizer
 from mistral_common.tokens.tokenizers.multimodal import image_from_chunk
 from transformers import AutoProcessor
 
-from vllm import (EngineArgs, LLMEngine, RequestOutput, SamplingParams,
+from vllm import RequestOutput, SamplingParams, TextPrompt, TokensPrompt
-                  TextPrompt, TokensPrompt)
 from vllm.multimodal import MultiModalDataBuiltins
 from vllm.multimodal.inputs import PlaceholderRange
 from vllm.sequence import Logprob, SampleLogprobs
@@ -28,7 +26,11 @@ from ...utils import check_logprobs_close
 if TYPE_CHECKING:
     from _typeshed import StrPath
 
-MODELS = ["mistralai/Pixtral-12B-2409"]
+PIXTRAL_ID = "mistralai/Pixtral-12B-2409"
+MISTRAL_SMALL_3_1_ID = "mistralai/Mistral-Small-3.1-24B-Instruct-2503"
+
+MODELS = [PIXTRAL_ID, MISTRAL_SMALL_3_1_ID]
+
 IMG_URLS = [
     "https://picsum.photos/id/237/400/300",
     "https://picsum.photos/id/231/200/300",
@@ -125,8 +127,10 @@ MAX_MODEL_LEN = [8192, 65536]
 FIXTURES_PATH = VLLM_PATH / "tests/models/fixtures"
 assert FIXTURES_PATH.exists()
 
-FIXTURE_LOGPROBS_CHAT = FIXTURES_PATH / "pixtral_chat.json"
+FIXTURE_LOGPROBS_CHAT = {
-FIXTURE_LOGPROBS_ENGINE = FIXTURES_PATH / "pixtral_chat_engine.json"
+    PIXTRAL_ID: FIXTURES_PATH / "pixtral_chat.json",
+    MISTRAL_SMALL_3_1_ID: FIXTURES_PATH / "mistral_small_3_chat.json",
+}
 
 OutputsLogprobs = list[tuple[list[int], str, Optional[SampleLogprobs]]]
 
@@ -166,12 +170,12 @@ def test_chat(
     model: str,
     dtype: str,
 ) -> None:
-    EXPECTED_CHAT_LOGPROBS = load_outputs_w_logprobs(FIXTURE_LOGPROBS_CHAT)
+    EXPECTED_CHAT_LOGPROBS = load_outputs_w_logprobs(
+        FIXTURE_LOGPROBS_CHAT[model])
     with vllm_runner(
             model,
             dtype=dtype,
             tokenizer_mode="mistral",
-            enable_chunked_prefill=False,
             max_model_len=max_model_len,
             limit_mm_per_prompt=LIMIT_MM_PER_PROMPT,
     ) as vllm_model:
@@ -183,70 +187,40 @@ def test_chat(
             outputs.extend(output)
 
     logprobs = vllm_runner._final_steps_generate_w_logprobs(outputs)
+    # Remove last `None` prompt_logprobs to compare with fixture
+    for i in range(len(logprobs)):
+        assert logprobs[i][-1] is None
+        logprobs[i] = logprobs[i][:-1]
     check_logprobs_close(outputs_0_lst=EXPECTED_CHAT_LOGPROBS,
                          outputs_1_lst=logprobs,
                          name_0="h100_ref",
                          name_1="output")
 
 
-@large_gpu_test(min_gb=80)
-@pytest.mark.parametrize("model", MODELS)
-@pytest.mark.parametrize("dtype", ["bfloat16"])
-def test_model_engine(vllm_runner, model: str, dtype: str) -> None:
-    EXPECTED_ENGINE_LOGPROBS = load_outputs_w_logprobs(FIXTURE_LOGPROBS_ENGINE)
-    args = EngineArgs(
-        model=model,
-        tokenizer_mode="mistral",
-        enable_chunked_prefill=False,
-        limit_mm_per_prompt=LIMIT_MM_PER_PROMPT,
-        dtype=dtype,
-    )
-    engine = LLMEngine.from_engine_args(args)
-
-    engine.add_request(uuid.uuid4().hex, ENGINE_INPUTS[0], SAMPLING_PARAMS)
-    engine.add_request(uuid.uuid4().hex, ENGINE_INPUTS[1], SAMPLING_PARAMS)
-
-    outputs = []
-    count = 0
-    while True:
-        out = engine.step()
-        count += 1
-        for request_output in out:
-            if request_output.finished:
-                outputs.append(request_output)
-
-        if count == 2:
-            engine.add_request(uuid.uuid4().hex, ENGINE_INPUTS[2],
-                               SAMPLING_PARAMS)
-        if not engine.has_unfinished_requests():
-            break
-
-    logprobs = vllm_runner._final_steps_generate_w_logprobs(outputs)
-    check_logprobs_close(outputs_0_lst=EXPECTED_ENGINE_LOGPROBS,
-                         outputs_1_lst=logprobs,
-                         name_0="h100_ref",
-                         name_1="output")
-
-
 @large_gpu_test(min_gb=48)
 @pytest.mark.parametrize(
     "prompt,expected_ranges",
     [(_create_engine_inputs_hf(IMG_URLS[:1]), [{
-        "offset": 10,
+        "offset": 11,
         "length": 494
     }]),
      (_create_engine_inputs_hf(IMG_URLS[1:4]), [{
-         "offset": 10,
+         "offset": 11,
          "length": 266
      }, {
-         "offset": 276,
+         "offset": 277,
          "length": 1056
      }, {
-         "offset": 1332,
+         "offset": 1333,
          "length": 418
      }])])
-def test_multi_modal_placeholders(
+def test_multi_modal_placeholders(vllm_runner, prompt,
-        vllm_runner, prompt, expected_ranges: list[PlaceholderRange]) -> None:
+                                  expected_ranges: list[PlaceholderRange],
+                                  monkeypatch) -> None:
+
+    # This placeholder checking test only works with V0 engine
+    # where `multi_modal_placeholders` is returned with `RequestOutput`
+    monkeypatch.setenv("VLLM_USE_V1", "0")
     with vllm_runner(
             "mistral-community/pixtral-12b",
             max_model_len=8192,