A capable MoE workhorse with strong multilingual chops, but its short context window and rising competition have eroded its value proposition.
72
Coding
75
Writing
68
Research
0
Images
58
Value
35
Long Context
Use this when
Teams needing strong multilingual capabilities and solid coding performance at a mid-tier price point without relying on OpenAI or Anthropic infrastructure.
Skip this if
You need to process long documents (>65K tokens), require vision/image understanding, or want the best coding performance per dollar — cheaper models now match or beat it there.
Pricing
$2.00/1M in
$6.00/1M out
→0%since Aug 2026
Context
66k tokens
Speed
Balanced
Available via Mistral API and as open weights (Apache 2.0 license) for self-hosting. The open-weight option is a key differentiator for privacy-sensitive or on-premise deployments. API pricing at $2/$6 per million tokens is mid-range but faces pressure from newer, cheaper alternatives.
Strong multilingual performance across French, Spanish, Italian, German, and other European languages — notably better than GPT-3.5-class models
MoE architecture delivers high-quality outputs with fewer active parameters, keeping latency competitive for its capability tier
Solid function-calling and instruction-following, making it reliable for agentic pipelines
Open-weight availability means it can be self-hosted, reducing vendor lock-in compared to closed models
Weaknesses
65K context window is noticeably limited compared to Gemini 3.1 Pro (1M+) or Claude Sonnet 4.6 (200K), making it a poor fit for long-document work
Coding and reasoning benchmarks trail GPT-4o and Claude Sonnet 4.6 at similar or lower price points, reducing its competitive edge
No native multimodal (image/vision) support, limiting its use in mixed-media workflows
Real-world use cases
What people actually use Mixtral 8x22B Instruct for.
Drafting and translating marketing copy simultaneously across French, Spanish, and Italian markets
Building a function-calling agent for structured data extraction from business documents
Generating and reviewing Python or TypeScript code for mid-complexity backend features
How Mixtral 8x22B Instruct compares
The nearest models people weigh against it, and what actually separates them.
vs Mistral Large 3 2512 — Against Mistral Large 3 2512 (Mistral), Mixtral 8x22B Instruct costs about 75% more per token and gives up 4x on context. Mistral Large 3 2512 is the one to check first if the price difference matters more than the ceiling.
vs Mistral Large 4 — Against Mistral Large 4 (Mistral), Mixtral 8x22B Instruct costs about 65% more per token and gives up 8x on context. Mistral Large 4 is the one to check first if the price difference matters more than the ceiling.
vs Claude 3.5 Sonnet — Against Claude 3.5 Sonnet (Anthropic), Mixtral 8x22B Instruct runs about 78% cheaper per token and gives up 3.1x on context. Take Mixtral 8x22B Instruct unless you specifically need what Claude 3.5 Sonnet does better.
Price History
Mixtral 8x22B Instruct pricing over time
→0% since Aug 4
90 data points · tracked daily since Aug 4, 2026
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Start using Mixtral 8x22B Instruct
Teams needing strong multilingual capabilities and solid coding performance at a mid-tier price point without relying on OpenAI or Anthropic infrastructure.. Start free — no card required.
Recommendations are made independently based on real-world use and public benchmarks. See our disclosures for details.
Compare alternatives
Similar models worth checking before you commit.
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Mistral Large 3 2512
Mistral Large 3 2512 is Mistral's flagship dense model updated in December 2025, offering strong multilingual reasoning and coding capabilities at a significantly reduced price point compared to its predecessor. It targets enterprise workloads that need high-quality outputs without paying top-tier frontier model prices.
Verdict
The best price-per-quality ratio in the non-mini flagship tier, especially for multilingual and long-context enterprise tasks.
Quality score
69%
Pricing
$0.50/1M in
$1.50/1M out
Speed
Balanced
3/5 speed
Context
262k tokens
Pricing of $0.50 input / $1.50 output per 1M tokens places it firmly in the budget-flagship category. Available via Mistral API (La Plateforme) and major cloud providers. December 2025 update ('2512') improves instruction following over the earlier 2407 release.
Multilingual enterprise tasks, code generation, and long-document analysis where cost efficiency matters more than absolute state-of-the-art performance.
Mistral's October 6, 2026 flagship, in public preview: a natively multimodal mixture-of-experts model with about 1 trillion total parameters, open weights promised for later in October, at $0.68/$2.09 per 1M.
Verdict
Mistral's open-weight flagship, cheap but still in preview.
Quality score
83%
Pricing
$0.68/1M in
$2.09/1M out
Speed
Balanced
3/5 speed
Context
524k tokens
Hosted preview launched October 6, 2026 on Mistral's API and Mistral Studio; open weights scheduled for late October. Gateway id mistral/mistral-large-4. $0.68/$2.09 per 1M. 524,288 context, 262,144 max output; text and image input. Mixture-of-experts, roughly 1 trillion total parameters (reports of active parameters vary from 49B to 52B). Vals AI index: 48.05%, 32nd of 44. Verified October 10, 2026.
Open weightsMultimodalEuropeanBudgetNew
Best for
European-hosted and open-weight deployments that need a frontier-class model
Claude 3.5 Sonnet is Anthropic's mid-cycle flagship model, balancing strong reasoning, coding, and instruction-following with a 200K context window. It sits between Haiku and Opus in Anthropic's lineup, offering near-flagship quality at a lower cost than top-tier models.
Verdict
One of the best models for coding and complex instruction-following, but its premium pricing demands premium use cases.
Quality score
81%
Pricing
$6.00/1M in
$30.00/1M out
Speed
Balanced
3/5 speed
Context
200k tokens
Pricing at $6 input / $30 output per million tokens is significantly higher than GPT-4o ($2.50/$10). Best accessed via Anthropic API or Amazon Bedrock. Claude 3.5 Sonnet (October 2024 version) supersedes the June 2024 release with improved performance.
Pricing moves, ranking shifts, and capability updates.
New ModelMar 27, 2026
Mistral: Mixtral 8x22B Instruct — added to UseRightAI
Mistral: Mixtral 8x22B Instruct (Mistral) is now indexed. A capable MoE workhorse with strong multilingual chops, but its short context window and rising competition have eroded its value proposition.
Mixtral 8x22B Instruct costs $2 per million input tokens and $6 per million output tokens on the API. A month of 10M input and 2M output tokens runs about $32.00 at list price, before any batch or caching discounts.
What is Mixtral 8x22B Instruct best for?
Mixtral 8x22B Instruct is best for teams needing strong multilingual capabilities and solid coding performance at a mid-tier price point without relying on openai or anthropic infrastructure.. It is a strong fit when that workflow matters more than the tradeoffs around balanced pricing and balanced speed.
When should I avoid Mixtral 8x22B Instruct?
You need to process long documents (>65K tokens), require vision/image understanding, or want the best coding performance per dollar — cheaper models now match or beat it there.
What is a cheaper alternative to Mixtral 8x22B Instruct?
Mistral Large 4 (Mistral) at $0.68/1M/1M input against Mixtral 8x22B Instruct's $2.00/1M/1M — roughly 65% less per token all in. Mistral's open-weight flagship, cheap but still in preview. Compare it first if Mixtral 8x22B Instruct's pricing is the thing stopping you.
What is a faster alternative to Mixtral 8x22B Instruct?
Mistral Large 3 2512 — balanced against Mixtral 8x22B Instruct's balanced, with 262k tokens of context. Worth the swap when response time is what your users notice rather than the last few points of reasoning depth.
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