phi-4 vs GLM OCR
At a Glance
| Compare |  phi-4Microsoft |  GLM OCRZ.ai |
|---|---|---|
| Pricing and Limits | ||
| Input priceFrom · USD / 1M tokens | $0.070Deepinfra ↗ · Sep 23, 2026 | Not reported |
| Output priceFrom · USD / 1M tokens | $0.14Deepinfra ↗ · Sep 23, 2026 | Not reported |
| Context windowMaximum documented tokens | 16K | 131K |
| Model facts checked | Aug 28, 2026View model evidence → | Aug 28, 2026View model evidence → |
Token prices are the lowest available sourced USD rates; input and output may use different providers. Cost ranking estimates output spend on LiveBench, not a full request bill. Ranking methodology →
Available Benchmarks
Side-by-Side Facts
| Field | phi-4 | GLM-OCR |
|---|---|---|
| Developer | Microsoft | Z.ai |
| Family | Phi 4 | Glm OCR |
| Model | phi-4 | GLM-OCR |
| Version | phi-4 | GLM-OCR |
| Lifecycle | active | active |
| Released | 2024-12-12 | Unknown |
| Knowledge cutoff | Unknown | Unknown |
| Input modalities | Text | Text, Image |
| Output modalities | Text | Text |
| Context window | 16K | 131K |
| Total parameters | 14.7B | 1.3B |
| Active parameters | Unknown | Unknown |
| License | mit | mit |
| Open weights | Yes | Yes |
| API available | Yes | Yes |
| Self-hostable | Yes | Yes |
| Provider access | Deepinfra (Standard), Hugging Face (Standard), Openrouter (Standard) | Together Ai (Standard) |
| Capabilities | chat, generation | chat, generation, tools |
phi-4 Capabilities
GLM OCR Capabilities
Related Comparisons
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|---|---|---|---|
phi-4Microsoft | vs |  GPT-6 AstraOpenAI | cross-developer peerstext |
Claude Fable 5.1Anthropic | vs | phi-4Microsoft | cross-developer peerstext |
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 DeepSeek-V4.1-FlashDeepSeek | vs | phi-4Microsoft | cross-developer peerstext |
phi-4Microsoft | vs | Grok 4.6xAI | cross-developer peerstext |
phi-4Microsoft | vs |  Qwen3.8-MaxQwen | cross-developer peerstext |
phi-4Microsoft | vs |  Kimi-K3Moonshot AI | cross-developer peerstext |
 MiniMax-M3MiniMax | vs | phi-4Microsoft | cross-developer peerstext |
phi-4Microsoft | vs | GLM-5.3Z.ai | cross-developer peerstext |
phi-4Microsoft | vs |  Hy4 previewTencent | cross-developer peerstext |
Seed 2.1 ProByteDance Seed | vs | phi-4Microsoft | cross-developer peerstext |
phi-4Microsoft | vs |  Mistral Large 3Mistral AI | cross-developer peerstext |
Primary Evidence
Sources and Freshness
Questions
phi-4 vs GLM OCR FAQs
Is phi-4 or GLM OCR better for coding?+
This comparison does not currently contain a protocol-matched coding benchmark for both phi-4 and GLM OCR, so Model Markets cannot name a coding leader from pricing, context size, or capability labels alone.
Which is cheaper, phi-4 or GLM OCR?+
Only phi-4 has a directly sourced input price: $0.070 per million tokens. Only phi-4 has a directly sourced output price: $0.14 per million tokens.
Which has a larger context window, phi-4 or GLM OCR?+
GLM OCR has the larger sourced context window. phi-4 supports 16K and GLM OCR supports 131K.
Which performs better in benchmarks, phi-4 or GLM OCR?+
There is no overall benchmark winner: At least two independently verified, protocol-matched benchmarks are required for an overall winner.
Can phi-4 or GLM OCR be self-hosted?+
Both models have the same recorded self-hosting status: supported. phi-4 is open weight; GLM OCR is open weight.
Can phi-4 and GLM OCR understand images?+
phi-4 is not documented with image input; GLM OCR is documented with image input. This reflects supported input modalities, not vision quality.
Which can generate longer answers, phi-4 or GLM OCR?+
Neither has a larger sourced maximum output. phi-4 is — and GLM OCR is —.
Do phi-4 and GLM OCR support reasoning and tool use?+
phi-4: none of these features are definitively sourced. GLM OCR: tool calling and image input. Feature support does not establish relative quality.
Which is available from more inference providers, phi-4 or GLM OCR?+
phi-4 has 3 sourced provider routes; GLM OCR has 1, so phi-4 has broader tracked availability.
Which offers better value, phi-4 or GLM OCR?+
There is no universal value winner. Compare the input and output prices above with the matched benchmark result for your workload: cheaper tokens can be offset by different quality, token usage, latency, or provider availability.