KI‑Modell‑Intelligenz

Mistral Small 4 119B Thinking

nano-gpt/small-4-119b-2603-thinking

Von nano-gpt · veröffentlicht 2026-03-17

⚠ Dies ist ein Community-Finetune oder Derivat — keine offizielle Anbieter-Veröffentlichung.

$0.400
Eingabe / 1 Mio. Tokens
$1.40
Ausgabe / 1 Mio. Tokens
262K
Kontextfenster
16K
Max. Ausgabe

Prices in USD per 1M tokens. Unknown means the provider does not publish per-token pricing.

Fähigkeiten

Tool CallingReasoningStrukturierte AusgabeAnhängeOffene Gewichte? Temperatur-Steuerung
Modalitäten: Eingabe text, image · Ausgabe text

Model fit scores

0–100 · higher is better

These scores reward declared capabilities, context size, price and provider availability — they are not benchmark results. Use them as a directional signal alongside your own evaluation.

Coding79
  • Tool calling40/40
  • Structured output20/20
  • Reasoning10/10
  • Context window (100K → 1M)8/20
  • Provider availability1/10
Agents86
  • Tool calling35/35
  • Structured output25/25
  • Reasoning15/15
  • Output token limit10/15
  • Provider availability1/10
JSON / structured output86
  • Structured output / JSON mode50/50
  • Tool calling20/20
  • Temperature control0/10
  • Price-friendly for high-volume16/20
Cost efficiency56
  • Headline price (log-scaled)56/95
  • Has prompt-cache pricing0/5
Long context61
  • Context window (100K → 2M)51/90
  • Has published price for full window10/10
Vision82
  • Accepts image input50/50
  • Context window (10K → 1M)21/30
  • Has published price10/10
  • Provider availability1/10
Production-readiness50
  • Number of independent providers5/40
  • Has published per-token price20/20
  • Context window ≥ 8K15/15
  • No data inconsistencies across providers10/10
  • Official model (not derivative)0/15

Cost Efficiency Index

Open full calculator →

Estimated cost using the recommended provider's headline rate. Each scenario fixes average input/output tokens — the assumptions are shown in the third column.

ScenarioCostAssumption
RAG answer
per 1,000 RAG answers
$2.70
< $0.01 per request
5K input tokens (query + 4 retrieved chunks of ~1K each) and a 500-token answer. Typical SaaS knowledge-base bot.
Support ticket triage
per 10,000 tickets
$5.40
< $0.01 per request
1K input tokens (ticket body + system prompt) and a 100-token JSON classification reply. High-volume customer support.
Data extraction
per 1,000 documents
$1.50
< $0.01 per request
2K input tokens (a single document page) and a 500-token JSON extraction. ETL / invoice / form pipelines.
Code review
per 1,000 PRs
$4.60
< $0.01 per request
8K input tokens (diff + surrounding files) and a 1K-token review comment. PR-bot workloads.
Agent step
per 1,000 steps
$5.64
< $0.01 per request
12K input tokens (long-running tool history) and a 600-token tool-call decision. Cost per agent step.

Preis-Details

Empfohlene Preise von nano-gpt · mistralai/mistral-small-4-119b-2603:thinking

$0.400
Eingabe
$1.40
Ausgabe

Bei 1 Anbietern verfügbar

AnbieterAnbieter-Modell-IDEingabe / 1MAusgabe / 1MKontextVeröffentlicht
NanoGPT
nano-gpt
mistralai/mistral-small-4-119b-2603:thinking$0.400$1.40262K2026-03-17

Frequently asked questions

How much does Mistral Small 4 119B Thinking cost?

Mistral Small 4 119B Thinking costs $0.400 per 1M input tokens and $1.40 per 1M output tokens, sourced from nano-gpt. Cache reads, audio tokens and >200K-context tiers (where applicable) are listed in the Pricing detail block above.

What is the context window of Mistral Small 4 119B Thinking?

Mistral Small 4 119B Thinking has a context window of 262K tokens, with a max output of 16K tokens per reply. This is the total combined size of prompt + completion.

Does Mistral Small 4 119B Thinking support tool calling?

Yes. Mistral Small 4 119B Thinking supports tool calling (function calling). This makes it suitable for production agent and automation workloads where the model has to invoke external functions reliably.

Does Mistral Small 4 119B Thinking support structured output / JSON mode?

Yes. Mistral Small 4 119B Thinking supports structured output / JSON-schema-constrained decoding. This makes it suitable for production agent and automation workloads where the model has to invoke external functions reliably.

Can Mistral Small 4 119B Thinking accept image input?

Yes. Mistral Small 4 119B Thinking accepts both text and image input. Vision pricing per image is usually billed on top of the regular token rate — check nano-gpt's docs for the exact rule.

Is Mistral Small 4 119B Thinking open-weight?

No. Mistral Small 4 119B Thinking is a proprietary model — only nano-gpt (and any approved hosting partners) can serve it. The pricing above reflects the cheapest API access.

What are the best alternatives to Mistral Small 4 119B Thinking?

If Mistral Small 4 119B Thinking doesn't fit, consider ERNIE X1.1, Brave (Research), MiroThinker 1.7 Deep Research Mini. Each one targets the same use case — see the Related links below for direct head-to-head pages.

Where does this data come from?

All numbers are normalised into a single canonical model record and reconciled with each provider's official documentation. We re-pull daily and write any changes (price, context, capability) to the /changelog page.

Zuletzt aktualisiert:

Pricing and capabilities are refreshed daily and reconciled against each provider's official documentation. Always verify critical production decisions with the provider directly.