Mistral · Balanced
Mistral Code Latest
Mistral Code Latest is Mistral's direct API alias for codestral-2508, a low-latency coding model for code generation, completion, fill-in-the-middle workflows, function calling, and structured output.
- Tools
- Structured output
- Input
- Text
- Output
- Text
- Discovery tier
- Balanced
Pricing
USD per 1M tokens- Input
- $0.30
- Output
- $0.90
Reference prices as published by the model provider. API example
Specifications
- Context window
- 256K
- Max output
- 32.8K
Side by side
Mistral Code Latest compared
Specifications, prices, speed and benchmark scores next to each other. Benchmarks below show every compared model too.
| Mistral Code LatestMistralThis model | Mistral Code Agent LatestMistralRemove | |
|---|---|---|
| Provider | Mistral | Mistral |
| Discovery tier | Balanced | Open weights |
| Added | Jun 2, 2026 | Jun 2, 2026 |
| Limits | ||
| Context window | 256K | 262.14KBest |
| Max output | 32.77K | 32.77K |
| Average output | — | 316 tokens |
| Pricing, USD per 1M tokens | ||
| Input | $0.30Best | $0.40 |
| Output | $0.90Best | $2.00 |
| Performance | ||
| Request success (24h) | — | 100.0% |
| Benchmark indexes | ||
| Intelligence Index | — | 8.6 |
| Coding Index | — | 31.3 |
| Math Index | — | 36.7 |
| Capabilities | ||
| Tools | Yes | Yes |
| Structured output | Yes | Yes |
| Reasoning effort | — | — |
Public evaluations
Benchmarks
Independent evaluation results, with how each score ranks among the models in the Noumen catalog.
- Mistral Code Latest
- Mistral Code Agent Latest
Intelligence Index
- Mistral Code Latest—
- Mistral Code Agent Latest8.6
Indexes
Coding Index
Composite of the coding evaluations
- Mistral Code Latest: —
- Mistral Code Agent Latest: 31.3
Math Index
Composite of the math evaluations
- Mistral Code Latest: —
- Mistral Code Agent Latest: 36.7
Agentic work
AutomationBench-AA
Workflow automation, penalized for guardrail violations
- Mistral Code Latest: —
- Mistral Code Agent Latest: 3.1%
AutomationBench-AA tasks completed
Workflows finished end to end without a guardrail violation
- Mistral Code Latest: —
- Mistral Code Agent Latest: 0.0%
AA-Briefcasev1.1
Agentic knowledge work, rated head to head
- Mistral Code Latest: —
- Mistral Code Agent Latest: 482 Elo
GDPval-AAv2.1
Economically valuable occupational tasks, rated head to head
- Mistral Code Latest: —
- Mistral Code Agent Latest: 544 Elo
Document reasoning
GDP.pdf
Professional reasoning over PDF documents, all-pass rate
- Mistral Code Latest: —
- Mistral Code Agent Latest: 2.4%
AA-LCRv1.1
Reasoning across long documents
- Mistral Code Latest: —
- Mistral Code Agent Latest: 32.3%
Reasoning and knowledge
Humanity’s Last Exam
Expert-level questions across academic fields
- Mistral Code Latest: —
- Mistral Code Agent Latest: 3.6%
GPQA Diamond
Graduate-level science questions
- Mistral Code Latest: —
- Mistral Code Agent Latest: 59.4%
MMLU-Pro
Multi-subject knowledge and reasoning
- Mistral Code Latest: —
- Mistral Code Agent Latest: 76.2%
IFBench
Following precise output instructions
- Mistral Code Latest: —
- Mistral Code Agent Latest: 38.1%
Coding
Terminal-Benchv4.0
Practical software engineering in a terminal
- Mistral Code Latest: —
- Mistral Code Agent Latest: 0.0%
SciCode
Scientific computing in Python
- Mistral Code Latest: —
- Mistral Code Agent Latest: 32.8%
LiveCodeBench
Recent competitive programming problems
- Mistral Code Latest: —
- Mistral Code Agent Latest: 44.8%
Math
AIME 2025
Competition mathematics, 2025 problems
- Mistral Code Latest: —
- Mistral Code Agent Latest: 36.7%
Legacy evaluations
Terminal-Bench Hard
Earlier terminal task suite
- Mistral Code Latest: —
- Mistral Code Agent Latest: 18.9%
τ²-Bench Telecom
Tool use in a customer-support simulation
- Mistral Code Latest: —
- Mistral Code Agent Latest: 24.9%
AA-LCR (unversioned)
Long-context reasoning, earlier grading
- Mistral Code Latest: —
- Mistral Code Agent Latest: 32.3%
Scores from Artificial Analysis, updated Oct 26, 2026. Artificial Analysis
Live routing data
Performance and reliability
Recent averages across requests routed for this model. Your own speed depends on prompt length, reasoning effort and load.
- Prompt cache hits
- 0.0%
Cache hits are the share of input tokens recently served from a prompt cache across all requests. They are not a forecast of your own hit rate.
Developers
Use it through the API
Noumen’s API is OpenAI-compatible: any Chat Completions client works with a base URL and a key.
curl https://www.noumen.xyz/api/v1/chat/completions \
-H "Authorization: Bearer $NOUMEN_API_KEY" \
-H "Content-Type: application/json" \
-d '{
"model": "mistral-code-latest",
"messages": [{ "role": "user", "content": "Explain this stack trace." }]
}'import os
from openai import OpenAI
client = OpenAI(base_url="https://www.noumen.xyz/api/v1", api_key=os.environ["NOUMEN_API_KEY"])
reply = client.chat.completions.create(
model="mistral-code-latest",
messages=[{"role": "user", "content": "Explain this stack trace."}],
)
print(reply.choices[0].message.content)Mistral
Related models
Other Mistral models, starting with the same family.