Multilingual AI models: all 239 handle more than English

Multilingual
Services found: 239
#AI modelCapabilitiesAPI $/1M (in / out)Context windowPrice / moOutput $/1MOverviewVisit site
141

Kimi K2.6

Moonshot AI
Text & chatVisionReasoning
$0.95 / $4262.1K tokensAPI only4View
142

Claude Opus 4.6

Anthropic
Text & chatVisionReasoning
$5 / $251M tokensAPI only25View
143

Ling 3.0 Flash

InclusionAI
Text & chatVisionLow latency
$0.021 / $0.063262.1K tokensAPI only0.063View
144

GPT-5.6 Sol Pro

OpenAI
Text & chatVisionReasoning
$2 / $101.05M tokensAPI only10View
145

Laguna XS 2.1

Poolside
Text & chatCodingMultilingual
$0.06 / $0.12262.1K tokensAPI only0.12View
146

GPT-6 Astra Pro

OpenAI
Text & chatVisionReasoning
$10 / $501.05M tokensAPI only50View
147

Claude Opus 4.7

Anthropic
Text & chatVisionReasoning
$5 / $251M tokensAPI only25View
148

Qwen3.5-Flash

Qwen
Text & chatVisionVideo
$0.065 / $0.261M tokensAPI only0.26View
149

Kimi K2.5

Moonshot AI
Text & chatVisionReasoning
$0.45 / $2.25262.1K tokensAPI only2.25View
150

Qwen3.6 35B A3B

Qwen
Text & chatVisionVideo
$0.1 / $0.9262.1K tokensAPI only0.9View
151

GLM 4.7

Z.ai
Text & chatStructured JSON outputPrompt caching
$0.4 / $1.75204.8K tokensAPI only1.75View
152

GPT-5.2

OpenAI
Text & chatVisionReasoning
$1.75 / $14400K tokensAPI only14View
153

Qwen3.5-35B-A3B

Qwen
Text & chatVisionVideo
$0.3125 / $1.25262.1K tokensAPI only1.25View
154

GLM 5

Z.ai
Text & chatReasoningTool calling
$0.6 / $1.92204.8K tokensAPI only1.92View
155

Nemotron 3 Nano Omni

NVIDIA
Text & chatVisionAudio
$0 / $0256K tokensAPI only0View
156

Qwen3.5-9B

Qwen
Text & chatVisionVideo
$0.1 / $0.15262.1K tokensAPI only0.15View
157

Grok 4.20

xAI
Text & chatVisionReasoning
$1.25 / $2.52M tokensAPI only2.5View
158

Qwen3 VL 32B Instruct

Qwen
Text & chatVisionReasoning
$0.104 / $0.416131.1K tokensAPI only0.416View
159

MiniMax M2.5

MiniMax
Text & chatReasoningTool calling
$0.27 / $1.08204.8K tokensAPI only1.08View
160

Qwen3 VL 235B A22B Instruct

Qwen
Text & chatVisionReasoning
$0.21 / $1.9262.1K tokensAPI only1.9View

Browse by need

Multilingual capability is now table stakes: all 239 models in this rating handle languages beyond English at production quality, Arabic included. The interesting question is no longer whether a model speaks your language but how efficiently it tokenises it.

Non-Latin scripts consume more tokens per word than English, so the same Arabic text costs more to process than its English equivalent. That makes the cheap end of this list - output from $0.25 per million - disproportionately attractive for high-volume multilingual work, and it makes prompt caching worth checking if your system prompt is long.

Tokenisation, not fluencyEvery model speaks the language; the difference is how many tokens it burns doing it.
Arabic costs moreNon-Latin scripts inflate token counts, so the same text bills higher than its English version.
Caching helps most hereA long multilingual system prompt is exactly what prompt caching was designed for.

Models with this capability

How to choose

  • Measure cost on real text in your language, not on English benchmarks.
  • Check output quality on dialect and register, not just on literal accuracy.
  • Prefer models with a free tier so you can test on your own corpus before paying.
  • For regulated translation, compare against a dedicated translation model.

Common mistakes

Assuming English pricing appliesA budget that works in English can overrun by half again in Arabic.
Skipping native reviewFluent output hides subtle register errors that only a native reader catches.

Who this suits

Gulf-facing productsArabic and English in one interface, with pricing that survives both.
Global supportOne model covering the whole ticket queue instead of per-language routing.
Content teamsDrafting in one language and adapting rather than translating.

Frequently asked questions

Does Arabic cost more than English?

Yes. Non-Latin scripts use more tokens per word, so the same text bills higher. Budget models and prompt caching offset it.

Which models are strongest in Arabic?

The frontier tier handles it best, and regional families — Qwen, GLM, Falcon — are trained with heavier non-English weighting.

Is a translation model better than a multilingual one?

For contracts and regulated text, yes. For everyday work a general mid-tier model is cheaper and good enough.

Which languages are weakest?

Low-resource languages remain uneven across all vendors. Test rather than assume.

Does a bigger model speak better?

Usually yes on nuance, but the gap narrows for straightforward everyday text.

Frequently searched

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