Granite Embedding 30m English vs Solar Pro 4
At a Glance
| Compare | Solar Pro 4Upstage | |
|---|---|---|
| Pricing and Limits | ||
| Input priceFrom · USD / 1M tokens | Not reported | $0.090Upstage ↗ · Sep 18, 2026 |
| Output priceFrom · USD / 1M tokens | Not reported | $0.36Upstage ↗ · Sep 18, 2026 |
| Context windowMaximum documented tokens | 1K | 524K |
| Model facts checked | Aug 28, 2026View model evidence → | Sep 18, 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 | granite-embedding-30m-english | Solar Pro 4 |
|---|---|---|
| Developer | IBM | Upstage |
| Family | Granite Embedding 30m English | Solar Pro |
| Model | granite-embedding-30m-english | Solar Pro 4 |
| Version | granite-embedding-30m-english | Solar Pro 4 |
| Lifecycle | active | active |
| Released | 2025-08-29 | 2026-08-14 |
| Knowledge cutoff | Unknown | Unknown |
| Input modalities | Text | Text |
| Output modalities | Embedding | Text |
| Context window | 1K | 524K |
| Total parameters | 30.3M | Unknown |
| Active parameters | Unknown | Unknown |
| License | apache-2.0 | Unknown |
| Open weights | Yes | No |
| API available | Yes | Yes |
| Self-hostable | Yes | Yes |
| Provider access | Hugging Face (Standard) | Upstage (Standard) |
| Capabilities | embeddings | agents, chat, generation, reasoning, structured_outputs, tools |
| Supported languages | Unknown | English, Korean, Japanese |
| Training data cutoff | Unknown | February 2026 |
Granite Embedding 30m English Capabilities
Solar Pro 4 Capabilities
Primary Evidence
Sources and Freshness
Questions
Granite Embedding 30m English vs Solar Pro 4 FAQs
Is Granite Embedding 30m English or Solar Pro 4 better for coding?+
This comparison does not currently contain a protocol-matched coding benchmark for both Granite Embedding 30m English and Solar Pro 4, so Model Markets cannot name a coding leader from pricing, context size, or capability labels alone.
Which is cheaper, Granite Embedding 30m English or Solar Pro 4?+
Only Solar Pro 4 has a directly sourced input price: $0.090 per million tokens. Only Solar Pro 4 has a directly sourced output price: $0.36 per million tokens.
Which has a larger context window, Granite Embedding 30m English or Solar Pro 4?+
Solar Pro 4 has the larger sourced context window. Granite Embedding 30m English supports 1K and Solar Pro 4 supports 524K.
Which performs better in benchmarks, Granite Embedding 30m English or Solar Pro 4?+
There is no overall benchmark winner: At least two independently verified, protocol-matched benchmarks are required for an overall winner.
Can Granite Embedding 30m English or Solar Pro 4 be self-hosted?+
Both models have the same recorded self-hosting status: supported. Granite Embedding 30m English is open weight; Solar Pro 4 is not marked open weight.
Can Granite Embedding 30m English and Solar Pro 4 understand images?+
Granite Embedding 30m English is not documented with image input; Solar Pro 4 is not documented with image input. This reflects supported input modalities, not vision quality.
Which can generate longer answers, Granite Embedding 30m English or Solar Pro 4?+
Neither has a larger sourced maximum output. Granite Embedding 30m English is — and Solar Pro 4 is 131K.
Do Granite Embedding 30m English and Solar Pro 4 support reasoning and tool use?+
Granite Embedding 30m English: none of these features are definitively sourced. Solar Pro 4: reasoning and tool calling. Feature support does not establish relative quality.
Which is available from more inference providers, Granite Embedding 30m English or Solar Pro 4?+
Granite Embedding 30m English has 1 sourced provider route; Solar Pro 4 has 1, a tie.
Which offers better value, Granite Embedding 30m English or Solar Pro 4?+
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.