Head-to-Head Model Comparison

Pixtral Large vs Pixtral 12B

Benchmarks, API Token Pricing, Context Window & Speed Comparison

Reviewed by the GetInfoUs research teamLast reviewed: October 2026Editorial policy
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AI CompareAI BenchmarkToken PricingModel CostModel SpecsSWE-bench CodingModel VersusWhich AI ModelLLM Speed & LatencyReasoning ModelsExtended ThinkingPrompt Caching ROI
Pixtral Large vs Pixtral 12B: Benchmarks, Pricing & Speed Comparison

Pixtral Large by Mistral AI and Pixtral 12B 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, Pixtral 12B holds a notable pricing advantage for token ingestion. On output generation, Pixtral 12B is more economical per million generated tokens. In data-heavy architectures requiring extensive repository or document analysis, both models provide an identical memory horizon with 128K tokens. In latency-sensitive production environments, Pixtral 12B 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.

Head-to-Head Comparison

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Popular Matchups:
Mistral AI

Pixtral Large

Large VLM

Frontier 124B parameter multimodal model built on Mistral Large 2, engineered for dense document analysis, visual math, and agentic workflows.

Intelligence Index48 / 100
Input Token:

$2.00 / 1M

Output Token:

$6.00 / 1M

Context Window:

128K tokens

SWE-bench Verified:

38.5%

Mistral AI

Pixtral 12B

Open VLM

Mistral's premier open 12-billion parameter multimodal model natively trained on text and images with arbitrary aspect ratio vision encoding.

Intelligence Index40 / 100
Input Token:

$0.15 / 1M

Output Token:

$0.15 / 1M

Context Window:

128K tokens

SWE-bench Verified:

28%

Key Differences at a Glance

  • Pixtral 12B is 22.8x cheaper for API usage (input + output tokens combined).
  • Pixtral 12B is faster at 85 tok/s vs 70 tok/s.
  • Pixtral Large leads on SWE-bench coding (38.5% vs 28.0%).
Need definitions for token pricing, context, or benchmarks?Explore AI Glossary →
FeaturePixtral LargePixtral 12B
Intelligence Index
Composite reasoning & knowledge score (0-100)
4840
Provider
Mistral AIMistral AI
Input Price
Cost per million input tokens
$2.00 / 1M$0.15 / 1M
Output Price
Cost per million output tokens
$6.00 / 1M$0.15 / 1M
Blended Price
Weighted 7:2:1 cache:input:output per 1M
$1.70 / 1M$0.08 / 1M
Context Window
Maximum input + output tokens
128K tokens~192 A4 pages of text128K tokens~192 A4 pages of text
Max Output Tokens
Per single request
8K8K
Throughput Speed
Tokens generated per second
70 tok/s85 tok/s
SWE-bench Verified
Real-world software engineering
38.5%28%
GPQA Diamond
Graduate-level reasoning
55.4%43.8%
Cached Input Price
Prompt caching discount per 1M tokens
$1.00 / 1M$0.05 / 1M

Who Wins Where?

At-a-glance decision framework
Coding
Pixtral Large
+10.5% SWE-bench lead
Cost
Pixtral 12B
22.8x cheaper monthly runtime
Speed
Pixtral 12B
+21% faster generation
Context
Tied
128K tokens window

Empirical Head-to-Head Benchmark Scores

Official evaluation metrics verified by independent third-party research labs.

Pixtral LargePixtral 12B
SWE-bench Verified (Autonomous Coding)

Industry benchmark evaluating real-world GitHub issue resolution and multi-file debugging.

38.5%vs28%
GPQA Diamond (Doctorate-Level Science & Math)

Challenging questions created by domain experts to test complex PhD-level reasoning.

55.4%vs43.8%
MMLU-Pro (Multi-task Language Understanding)

Hardened reasoning and academic knowledge benchmark with reduced lucky-guess probability.

78%vs67.5%
LMSYS Chatbot Arena Elo

Crowdsourced human preference evaluation based on blind, head-to-head model battles.

1295ptsvs1225pts
Terminal-Bench (Agentic Coding & Terminal Use)

Autonomous multi-step tasks executed inside a real command-line terminal environment.

34%vs24%
AIME (Advanced Math Competition)

American Invitational Mathematics Examination — multi-step Olympiad-level reasoning.

65%vs48%
Long-Context Reasoning

Accuracy when reasoning over very large inputs that fill the model context window.

75%vs65%
Generation Speed (Throughput)

Tokens emitted per second during active generation streaming.

70 tok/s vs85 tok/s

Latency & Response Time

Time to first token (TTFT) and estimated end-to-end response time for a typical 500-token response.

Time to First Token (TTFT)Lower is better
Pixtral Large0.55s
Pixtral 12B0.45s
Est. End-to-End Response (500 tokens)TTFT + generation time
Pixtral Large7.69s
Pixtral 12B6.33s

Real-Time Interactive Token Cost Simulator

Adjust sliders to calculate projected monthly cloud API spending with prompt caching discounts.

100K / day
10K500K1M
30K / day
5K150K300K
50% cached
0% (Cold)50%90% (Warm)
Pixtral Large Monthly API Bill
$9.90 / month
$2/1M in · $6/1M out
Pixtral 12B Monthly API Bill
$0.43 / month
$0.15/1M in · $0.15/1M out
Pixtral 12B saves approximately $9.46 / month (96%) under this workload.22.8x Savings

Pixtral Large · Strengths & Key Advantages

  • World-class visual document reasoning matching proprietary multimodal leaders
  • Seamless parsing of high-resolution diagrams, complex financial spreadsheets, and schematics
  • 128K context window with open-weights availability
Considerations & Trade-offs
  • Substantial compute requirements for local cluster hosting (124B weights)
  • Higher API token pricing than lightweight Pixtral 12B

Pixtral 12B · Strengths & Key Advantages

  • Native image comprehension supporting multiple images and arbitrary aspect ratios
  • Open weights under Apache 2.0 license for unrestricted local hosting
  • Strong visual document OCR, chart parsing, and diagram understanding
Considerations & Trade-offs
  • Smaller capacity limits complex multi-step reasoning on dense schematics
  • Video and audio modalities not supported

Token Use & Task Economics

Estimated cost and token consumption to complete one representative agentic task.

MetricPixtral LargePixtral 12B
Cost per Task
Estimated USD to finish one task
$0.65$0.09
Output Tokens / Task
Tokens generated per task
35K25K
Reasoning Tokens / Task
Thinking tokens burned per task
0K0K

Technical Specifications

Architecture, release timeline, capabilities, and modalities.

FeaturePixtral LargePixtral 12B
Official API Model ID (SDK)pixtral-large-latestpixtral-12b-latest
API ProtocolOpenAI-Compatible REST / vLLM / SGLang / HuggingFace TGIOpenAI-Compatible REST / vLLM / SGLang / HuggingFace TGI
Release Date2024-112024-09
Knowledge CutoffOctober 2024August 2024
ArchitectureFrontier Vision-Language TransformerMultimodal Vision-Language Transformer
Parameters124B12B
Enterprise Rate Limits (RPM / TPM)Unlimited (Hardware-bound on self-hosted GPU) / 10,000 RPM Cloud · Unlimited local throughput / 10M+ TPM Managed CloudUnlimited (Hardware-bound on self-hosted GPU) / 10,000 RPM Cloud · Unlimited local throughput / 10M+ TPM Managed Cloud
Long-Context Tier (>128K/200K)Flat rate ($2/1M in) across full 128K windowFlat rate ($0.15/1M in) across full 128K window
Prompt Cache Policy & TTLCached input at $1/1M tokensCached input at $0.05/1M tokens
Computer Use / GUI AgentAPI / 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 CallingNative MCP Client/Server ready · Parallel function calling · 100% Strict JSON SchemaNative MCP Client/Server ready · Parallel function calling · 100% Strict JSON Schema
Web Search Grounding & SandboxSupported via external Tavily/Exa Search & E2B/Docker Sandbox toolsSupported via external Tavily/Exa Search & E2B/Docker Sandbox tools
Official Fine-Tuning SupportFull 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 BillingText BPE (~4 chars/token) · Vision (~258–765 tokens per image tile)Text BPE (~4 chars/token) · Vision (~258–765 tokens per image tile)
Quantization & Min GPU VRAMBF16 / FP16, FP8 Dynamic, INT4 AWQ / GPTQ, GGUF (Q4_K_M / Q8_0) · 77 GB VRAM (4-bit Quantized) · 267 GB VRAM (Native BF16)BF16 / FP16, FP8 Dynamic, INT4 AWQ / GPTQ, GGUF (Q4_K_M / Q8_0) · 7 GB VRAM (4-bit Quantized) · 26 GB VRAM (Native BF16)
Safety & Frontier ClassificationOpen-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 Control100% Air-Gapped On-Premises / Private VPC · Full HIPAA, GDPR & SOC2 Control
Input Modalitiestext, visiontext, vision
Output Modalitiestexttext

Pixtral Large vs Pixtral 12B: Quick Answers

Which is more intelligent, Pixtral Large or Pixtral 12B?

Pixtral Large is more intelligent. It scores 48 compared with 40 on the composite Intelligence Index.

Which model is faster?

Pixtral 12B is faster, generating 85 tokens per second compared with 70 tokens per second.

Which model is cheaper to run?

Pixtral 12B is cheaper at $0.08 per 1M tokens blended, compared with $1.70 (7:2:1 cache:input:output ratio).

Which model has lower latency?

Pixtral 12B has lower latency, with a time to first token of 0.45s compared with 0.55s.

Verdict

Verdict & Model Selection Recommendation: Choose Pixtral Large if your priority is Enterprise document understanding, financial visual audit, and sovereign multimodal automation. Its performance in demanding tasks justifies its operational token cost. Choose Pixtral 12B if your workflow prioritizes Document OCR, visual inspection agents, and open multimodal pipelines. For large-scale batch processing or customer-facing conversational interfaces, its balance of speed and economics delivers superior ROI.

Frequently asked questions

How does Pixtral Large compare to Pixtral 12B in API token pricing and cost per token?+

Pixtral Large costs $2.00 per 1M input tokens and $6.00 per 1M output tokens, whereas Pixtral 12B costs $0.15 input and $0.15 output. Overall, Pixtral 12B 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: Pixtral Large or Pixtral 12B?+

Both Pixtral Large and Pixtral 12B offer an identical context window of 128K tokens (~96k words). Both architectures provide equal capacity for large document ingestion, multi-file codebases, and extended multi-turn conversation histories.

Which AI model is better for software engineering and coding: Pixtral Large or Pixtral 12B?+

Pixtral Large scores 38.5% on SWE-bench Verified while Pixtral 12B scores 28%. For autonomous software engineering and multi-file debugging, Pixtral Large holds the verified benchmark lead.

What is the difference in reasoning capability and extended thinking between Pixtral Large and Pixtral 12B?+

Pixtral Large is optimized for low-latency direct generation. In contrast, Pixtral 12B focuses on standard fast inference.

How does inference speed (tokens per second) compare between Pixtral Large and Pixtral 12B?+

Pixtral Large generates approximately 70 tokens per second, while Pixtral 12B delivers 85 tokens per second. In latency-sensitive production environments, Pixtral 12B provides faster time-to-first-token (TTFT) and higher streaming response velocity.

Can you implement a tiered LLM routing setup combining Pixtral Large and Pixtral 12B to optimize costs?+

Yes! High-efficiency architectures route high-frequency routine classification and conversational tasks to Pixtral 12B to save operational costs, and dynamically escalate complex architectural queries or reasoning tasks to Pixtral Large. This tiered routing pattern cuts overall API bills by up to 70%.

AI Terminology & Guide
Explore Glossary →

Understand key metrics like context window, token pricing, reasoning mode, and SWE-bench scores in our comprehensive AI glossary.

Benchmark scores, token prices, and rate limits evolve rapidly as AI labs release model updates. Always verify current specifications and pricing on the official provider documentation.

Sources: GetInfoUs Independent AI Benchmarks & Official API Specs