Mistral Medium 3 vs Mistral Small 3
Benchmarks, API Token Pricing, Context Window & Speed Comparison
Related topics (12)
Mistral Medium 3 by Mistral AI and Mistral Small 3 by Mistral AI represent two of the frontier AI models analyzed in our comprehensive 2026 AI benchmark and LLM comparison. In this head-to-head evaluation, we examine API token pricing, context window specifications, inference speed (tokens per second), and empirical reasoning performance. From a pure economic perspective, Mistral Small 3 holds a notable pricing advantage for token ingestion. On output generation, Mistral Small 3 is more economical per million generated tokens. In data-heavy architectures requiring extensive repository or document analysis, Mistral Medium 3 provides an expanded memory horizon with 131K tokens. In latency-sensitive production environments, Mistral Small 3 leads in tokens-per-second throughput, making it ideal for real-time conversational agents and high-concurrency workflows. Below is the complete empirical head-to-head breakdown across cost, speed, context, and capability matrices.
Changez et Comparez les Modèles
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Mistral Medium 3
Équilibré d'entrepriseéquilibré d'entreprise modèle intégrant 131K contexte, multimodal vision, robust appel d'outils, et attractive $0.40/$2.00 tarification.
$0.40 / 1M
$2.00 / 1M
131.1K tokens
40.5%
Mistral Small 3
Petit et efficaceélevé-efficacité 24B ouvert modèle de fondation offrant rapide latence, faible mémoire empreinte, et d'entreprise-grade instruction adherence.
$0.10 / 1M
$0.30 / 1M
32K tokens
31.5%
Différences Clés en un Coup d’Œil
- Mistral Small 3 is 5.2x cheaper for API usage (input + output tokens combined).
- Mistral Medium 3 has a larger context window (131K vs 32K tokens).
- Mistral Small 3 is faster at 105 tok/s vs 85 tok/s.
- Mistral Medium 3 leads on SWE-bench coding (40.5% vs 31.5%).
| Caractéristique | Mistral Medium 3 | Mistral Small 3 |
|---|---|---|
Intelligence Index Composite reasoning & knowledge score (0-100) | 47 | 41 |
Provider | Mistral AI | Mistral AI |
Input Price Cost per million input tokens | $0.40 / 1M | $0.10 / 1M |
Output Price Cost per million output tokens | $2.00 / 1M | $0.30 / 1M |
Blended Price Weighted 7:2:1 cache:input:output per 1M | $0.35 / 1M | $0.09 / 1M |
Context Window Maximum input + output tokens | 131.1K tokens~197 A4 pages of text | 32K tokens~48 A4 pages of text |
Max Output Tokens Per single request | 16K | 8K |
Throughput Speed Tokens generated per second | 85 tok/s | 105 tok/s |
SWE-bench Verified Real-world software engineering | 40.5% | 31.5% |
GPQA Diamond Graduate-level reasoning | 57.5% | 46.5% |
Cached Input Price Prompt caching discount per 1M tokens | $0.10 / 1M | $0.05 / 1M |
Qui gagne où ?
At-a-glance decision frameworkScores de Benchmarks Vérifiés
Official evaluation metrics verified by independent third-party research labs.
Industry benchmark evaluating real-world GitHub issue resolution and multi-file debugging.
Challenging questions created by domain experts to test complex PhD-level reasoning.
Hardened reasoning and academic knowledge benchmark with reduced lucky-guess probability.
Crowdsourced human preference evaluation based on blind, head-to-head model battles.
Autonomous multi-step tasks executed inside a real command-line terminal environment.
American Invitational Mathematics Examination — multi-step Olympiad-level reasoning.
Accuracy when reasoning over very large inputs that fill the model context window.
Tokens emitted per second during active generation streaming.
Latence et Temps de Réponse
Time to first token (TTFT) and estimated end-to-end response time for a typical 500-token response.
Simulateur Interactif de Coût de Tokens
Adjust sliders to calculate projected monthly cloud API spending with prompt caching discounts.
Mistral Medium 3 · Strengths & Key Advantages
- Compelling prix-à-performances ratio ($0.40 entrée / $2.00 sortie)
- natif visuel compréhension à travers documents, schematics, et charts
- 131K fenêtre de contexte avec d'entreprise-grade function calling
Considerations & Trade-offs
- Trails de pointe phare modèles sur difficult competition mathematics
- à poids ouverts require multi-GPU setups pour complet précision
Mistral Small 3 · Strengths & Key Advantages
- Extremely faible API tarification ($0.10/$0.30) et léger local empreinte
- Snappy inférence vitesse exceeding 100 tokens/sec
- fiable function calling et classification précision
Considerations & Trade-offs
- 32K fenêtre de contexte limits profond dépôt scanning
- texte-seulement avec no image entrée capacités
Token Use & Task Economics
Estimated cost and token consumption to complete one representative agentic task.
| Metric | Mistral Medium 3 | Mistral Small 3 |
|---|---|---|
Cost per Task Estimated USD to finish one task | $0.35 | $0.08 |
Output Tokens / Task Tokens generated per task | 35K | 25K |
Reasoning Tokens / Task Thinking tokens burned per task | 0K | 0K |
Spécifications Techniques
Architecture, release timeline, capabilities, and modalities.
| Caractéristique | Mistral Medium 3 | Mistral Small 3 |
|---|---|---|
| Official API Model ID (SDK) | mistral-medium-3-latest | mistral-small-3-latest |
| API Protocol | OpenAI-Compatible REST / vLLM / SGLang / HuggingFace TGI | OpenAI-Compatible REST / vLLM / SGLang / HuggingFace TGI |
| Release Date | 2025-05 | 2025-01 |
| Knowledge Cutoff | March 2025 | December 2024 |
| Architecture | Enterprise Multimodal Transformer | Compact Dense Transformer |
| Parameters | Confidential (~70B) | 24B |
| Enterprise Rate Limits (RPM / TPM) | Unlimited (Hardware-bound on self-hosted GPU) / 10,000 RPM Cloud · Unlimited local throughput / 10M+ TPM Managed Cloud | Unlimited (Hardware-bound on self-hosted GPU) / 10,000 RPM Cloud · Unlimited local throughput / 10M+ TPM Managed Cloud |
| Long-Context Tier (>128K/200K) | Flat rate ($0.4/1M in) across full 131K window | Flat rate ($0.1/1M in) across full 32K window |
| Prompt Cache Policy & TTL | Cached input at $0.1/1M tokens | Cached input at $0.05/1M tokens |
| Computer Use / GUI Agent | API / CLI Tool-Use & DOM Agent ready (no raw pixel desktop click loop) | API / CLI Tool-Use & DOM Agent ready (no raw pixel desktop click loop) |
| MCP & Parallel Tool Calling | Native MCP Client/Server ready · Parallel function calling · 100% Strict JSON Schema | Native MCP Client/Server ready · Parallel function calling · 100% Strict JSON Schema |
| Web Search Grounding & Sandbox | Supported via external Tavily/Exa Search & E2B/Docker Sandbox tools | Supported via external Tavily/Exa Search & E2B/Docker Sandbox tools |
| Official Fine-Tuning Support | Full Weights SFT, LoRA, QLoRA, DPO & GRPO RL (Unsloth / Axolotl / Llama-Factory) | Full Weights SFT, LoRA, QLoRA, DPO & GRPO RL (Unsloth / Axolotl / Llama-Factory) |
| Multimodal Token Billing | Text BPE (~4 chars/token) · Vision (~258–765 tokens per image tile) | Text BPE (~4 chars/token) |
| Quantization & Min GPU VRAM | BF16 / FP16, FP8 Dynamic, INT4 AWQ / GPTQ, GGUF (Q4_K_M / Q8_0) · 43 GB VRAM (4-bit Quantized) · 151 GB VRAM (Native BF16) | BF16 / FP16, FP8 Dynamic, INT4 AWQ / GPTQ, GGUF (Q4_K_M / Q8_0) · 15 GB VRAM (4-bit Quantized) · 52 GB VRAM (Native BF16) |
| Safety & Frontier Classification | Open-Weights System Card + Customizable Guardrail Layer (Llama Guard / ShieldGemma) | Open-Weights System Card + Customizable Guardrail Layer (Llama Guard / ShieldGemma) |
| Enterprise Compliance (ZDR/HIPAA/SOC2) | 100% Air-Gapped On-Premises / Private VPC · Full HIPAA, GDPR & SOC2 Control | 100% Air-Gapped On-Premises / Private VPC · Full HIPAA, GDPR & SOC2 Control |
| Input Modalities | text, vision | text |
| Output Modalities | text | text |
Mistral Medium 3 vs Mistral Small 3: Réponses Rapides (FAQ)
Which is more intelligent, Mistral Medium 3 or Mistral Small 3?
Mistral Medium 3 is more intelligent. It scores 47 compared with 41 on the composite Intelligence Index.
Which model is faster?
Mistral Small 3 is faster, generating 105 tokens per second compared with 85 tokens per second.
Which model is cheaper to run?
Mistral Small 3 is cheaper at $0.09 per 1M tokens blended, compared with $0.35 (7:2:1 cache:input:output ratio).
Which model has lower latency?
Mistral Small 3 has lower latency, with a time to first token of 0.38s compared with 0.48s.
Which model has a larger context window?
Mistral Medium 3 has a larger context window, supporting 131.1K tokens compared with 32K tokens.
Verdict
Verdict & Model Selection Recommendation: Choose Mistral Medium 3 if your priority is Enterprise internal assistants, document workflow automation, and multimodal analytics. Its performance in demanding tasks justifies its operational token cost. Choose Mistral Small 3 if your workflow prioritizes High-volume customer support, classification pipelines, and low-latency chatbots. For large-scale batch processing or customer-facing conversational interfaces, its balance of speed and economics delivers superior ROI.
Questions fréquentes
How does Mistral Medium 3 compare to Mistral Small 3 in API token pricing and cost per token?+
Mistral Medium 3 costs $0.40 per 1M input tokens and $2.00 per 1M output tokens, whereas Mistral Small 3 costs $0.10 input and $0.30 output. Overall, Mistral Small 3 is the more cost-effective model for high-volume API pipelines. Both models support prompt caching discounts of up to 90% for repeated prompt prefixes.
Which model has a larger context window: Mistral Medium 3 or Mistral Small 3?+
Mistral Medium 3 supports a context window of 131K tokens (~98k words), while Mistral Small 3 supports 32K tokens (~24k words). Therefore, Mistral Medium 3 can process more textual data and document context in a single prompt.
Which AI model is better for software engineering and coding: Mistral Medium 3 or Mistral Small 3?+
Mistral Medium 3 scores 40.5% on SWE-bench Verified while Mistral Small 3 scores 31.5%. For autonomous software engineering and multi-file debugging, Mistral Medium 3 holds the verified benchmark lead.
What is the difference in reasoning capability and extended thinking between Mistral Medium 3 and Mistral Small 3?+
Mistral Medium 3 is optimized for low-latency direct generation. In contrast, Mistral Small 3 focuses on standard fast inference.
How does inference speed (tokens per second) compare between Mistral Medium 3 and Mistral Small 3?+
Mistral Medium 3 generates approximately 85 tokens per second, while Mistral Small 3 delivers 105 tokens per second. In latency-sensitive production environments, Mistral Small 3 provides faster time-to-first-token (TTFT) and higher streaming response velocity.
Can you implement a tiered LLM routing setup combining Mistral Medium 3 and Mistral Small 3 to optimize costs?+
Yes! High-efficiency architectures route high-frequency routine classification and conversational tasks to Mistral Small 3 to save operational costs, and dynamically escalate complex architectural queries or reasoning tasks to Mistral Medium 3. This tiered routing pattern cuts overall API bills by up to 70%.
Understand key metrics like context window, token pricing, reasoning mode, and SWE-bench scores in our comprehensive AI glossary.
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Les scores de benchmarks, tarifs par token et limites évoluent rapidement. Vérifiez toujours les spécifications actuelles sur la documentation officielle du fournisseur.
Sources: GetInfoUs Independent AI Benchmarks & Official API Specs