Multilingual AI models: all 239 handle more than English

Multilingual
Services found: 239
#AI modelCapabilitiesAPI $/1M (in / out)Context windowPrice / moOutput $/1MOverviewVisit site
201

Cydonia 24B V4.1

Thedrummer
Text & chatMultilingualProprietary API
$0.3 / $0.5131.1K tokensAPI only0.5View
202

Seed 2.1 Turbo

Bytedance Seed
Text & chatVisionVideo
$0.5 / $2.5262.1K tokensAPI only2.5View
203

GLM 4.6V

Z.ai
Text & chatVisionVideo
$0.3 / $0.9131.1K tokensAPI only0.9View
204

Aion-2.0

Aion Labs
Text & chatMultilingualProprietary API
$0.8 / $1.6131.1K tokensAPI only1.6View
205

GPT-5.1-Codex

OpenAI
Text & chatVisionCoding
$1.25 / $10400K tokensAPI only10View
206

MiniMax M2.1

MiniMax
Text & chatReasoningTool calling
$0.3 / $1.2204.8K tokensAPI only1.2View
207

Nano Banana Pro (Gemini 3 Pro Image)

Google
VisionAdjustable thinkingImage generation
$2 / $12131.1K tokensAPI only12View
208

MiniMax M2-her

MiniMax
Text & chatReasoningTool calling
$0.3 / $1.265.5K tokensAPI only1.2View
209

MiniMax M2

MiniMax
Text & chatReasoningTool calling
$0.255 / $1.02204.8K tokensAPI only1.02View
210

Hy-MT2-30B-A3B

Tencent
Text & chatMultilingualProprietary API
$0.074 / $0.2958.2K tokensAPI only0.295View
211

Perceptron Mk1

Perceptron
Text & chatVisionVideo
$0.15 / $1.532.8K tokensAPI only1.5View
212

GPT-5.5 Pro

OpenAI
Text & chatVisionReasoning
$30 / $1801.05M tokensAPI only180View
213

Seed 1.6

Bytedance Seed
Text & chatVisionVideo
$0.25 / $2262.1K tokensAPI only2View
214

Sonar Pro Search

Perplexity
Text & chatVisionReasoning
$3 / $15200K tokensAPI only15View
215

Fugu Ultra

Sakana
Text & chatVisionLong context 1M+
$5 / $301M tokensAPI only30View
216

GPT-5.1-Codex-Max

OpenAI
Text & chatVisionCoding
$1.25 / $10400K tokensAPI only10View
217

Qwen3 Max Thinking

Qwen
Text & chatReasoningAdjustable thinking
$0.78 / $3.9262.1K tokensAPI only3.9View
218

Seed-2.0-Code

Bytedance Seed
Text & chatVisionVideo
$0.5 / $3262.1K tokensAPI only3View
219

GPT Audio Mini

OpenAI
Text & chatAudioStructured JSON output
$0.6 / $2.4128K tokensAPI only2.4View
220

GPT-5 Image Mini

OpenAI
VisionImage generationStructured JSON output
$2.5 / $2400K tokensAPI only2View

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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