Jev vs GLM OCR
At a Glance
| Compare |  JevTypeSafe |  GLM OCRZ.ai |
|---|---|---|
| Pricing and Limits | ||
| Input priceFrom · USD / 1M tokens | $0.042TypeSafe ↗ · Sep 17, 2026 | Not reported |
| Output priceFrom · USD / 1M tokens | $0.000TypeSafe ↗ · Sep 17, 2026 | Not reported |
| Context windowMaximum documented tokens | 64K | 131K |
| Model facts checked | Sep 17, 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 | Jev | GLM-OCR |
|---|---|---|
| Developer | TypeSafe | Z.ai |
| Family | Jev | Glm OCR |
| Model | Jev | GLM-OCR |
| Version | Jev | GLM-OCR |
| Lifecycle | active | active |
| Released | 2026-09-15 | Unknown |
| Knowledge cutoff | Unknown | Unknown |
| Input modalities | Text, Model-specific input | Text, Image |
| Output modalities | Model-specific input | Text |
| Context window | 64K | 131K |
| Total parameters | Unknown | 1.3B |
| Active parameters | Unknown | Unknown |
| License | Unknown | mit |
| Open weights | No | Yes |
| API available | Yes | Yes |
| Self-hostable | No | Yes |
| Provider access | TypeSafe (Standard) | Together Ai (Standard) |
| Capabilities | calibrated-confidence, parallel-evaluation, structured_outputs, typed-decisions | chat, generation, tools |
| Maximum Choice cardinality | 255 options | Unknown |
| Default request rate limit | 1200 requests per minute | Unknown |
| State plus longest question limit | 32000 tokens | Unknown |
| Combined state and questions limit | 64000 tokens | Unknown |
| Default token rate limit | 250000 tokens per second | Unknown |
Jev Capabilities
GLM OCR Capabilities
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Primary Evidence
Sources and Freshness
Questions
Jev vs GLM OCR FAQs
Is Jev or GLM OCR better for coding?+
This comparison does not currently contain a protocol-matched coding benchmark for both Jev and GLM OCR, so Model Markets cannot name a coding leader from pricing, context size, or capability labels alone.
Which is cheaper, Jev or GLM OCR?+
Only Jev has a directly sourced input price: $0.042 per million tokens. Only Jev has a directly sourced output price: $0.000 per million tokens.
Which has a larger context window, Jev or GLM OCR?+
GLM OCR has the larger sourced context window. Jev supports 64K and GLM OCR supports 131K.
Which performs better in benchmarks, Jev or GLM OCR?+
There is no overall benchmark winner: At least two independently verified, protocol-matched benchmarks are required for an overall winner.
Can Jev or GLM OCR be self-hosted?+
GLM OCR is the only model in this pair currently marked as self-hostable. Jev is not marked open weight; GLM OCR is open weight.
Can Jev and GLM OCR understand images?+
Jev 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, Jev or GLM OCR?+
Neither has a larger sourced maximum output. Jev is — and GLM OCR is —.
Do Jev and GLM OCR support reasoning and tool use?+
Jev: 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, Jev or GLM OCR?+
Jev has 1 sourced provider route; GLM OCR has 1, a tie.
Which offers better value, Jev 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.