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 May 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 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.
vs Claude Fable 5 — Against Claude Fable 5 (Anthropic), Mixtral 8x22B Instruct runs about 87% cheaper per token, gives up 15.3x on context and answers faster. Take Mixtral 8x22B Instruct unless you specifically need what Claude Fable 5 does better.
Price History
Mixtral 8x22B Instruct pricing over time
→0% since May 30
90 data points · tracked daily since May 30, 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.
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.
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.
Anthropic's new Mythos-class flagship and the most capable coding model anyone can use — 80.3% SWE-Bench Pro, an 11-point jump over Opus 4.8. 1M context, 128K output, native parallel subagents. Released June 9, 2026.
Verdict
New global #1 — 80.3% SWE-Bench Pro, the most capable model generally available.
Quality score
98%
Pricing
$10.00/1M in
$50.00/1M out
Speed
Deliberate
2/5 speed
Context
1M tokens
Launched June 9, 2026 as the public, Mythos-class release. Available on the Claude API, Microsoft Foundry, and Google Vertex AI. Free for all users until June 22, 2026. Same underlying model as Claude Mythos 5, with safeguards that block specific high-risk cyber responses.
Coding leaderSWE-Bench Pro #1Mythos-classParallel subagentsAgenticLong contextPremiumNew
Best for
The hardest coding tasks, autonomous multi-step agents, and frontier-grade reasoning
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 3 2512 (Mistral) at $0.50/1M/1M input against Mixtral 8x22B Instruct's $2.00/1M/1M — roughly 75% less per token all in. The best price-per-quality ratio in the non-mini flagship tier, especially for multilingual and long-context enterprise tasks. Compare it first if Mixtral 8x22B Instruct's pricing is the thing stopping you.
What is a faster alternative to Mixtral 8x22B Instruct?
Claude 3.5 Sonnet — balanced against Mixtral 8x22B Instruct's balanced, with 200k 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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