Granite Embedding 278m Multilingual vs Qwen3.7 Flash
At a Glance
| Compare |  Qwen3.7 FlashQwen | |
|---|---|---|
| Pricing and Limits | ||
| Input priceFrom · USD / 1M tokens | $0.106IBM watsonx.ai ↗ · Aug 29, 2026 | $0.030Openrouter ↗ · Sep 23, 2026 |
| Output priceFrom · USD / 1M tokens | Not reported | $0.13Openrouter ↗ · Sep 23, 2026 |
| Context windowMaximum documented tokens | 1K | 1,000K |
| Model facts checked | Aug 28, 2026View model evidence → | Sep 3, 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-278m-multilingual | Qwen3.7 Flash |
|---|---|---|
| Developer | IBM | Qwen |
| Family | Granite Embedding 278m Multilingual | Qwen3 7 |
| Model | granite-embedding-278m-multilingual | Qwen3.7 Flash |
| Version | granite-embedding-278m-multilingual | Qwen3.7 Flash |
| Lifecycle | active | active |
| Released | 2024-12-18 | 2026-07-15 |
| Knowledge cutoff | Unknown | Unknown |
| Input modalities | Text | Text, Image, Video |
| Output modalities | Embedding | Text |
| Context window | 1K | 1,000K |
| Total parameters | 278M | Unknown |
| Active parameters | Unknown | Unknown |
| License | apache-2.0 | Unknown |
| Open weights | Yes | No |
| API available | Yes | Yes |
| Self-hostable | Yes | No |
| Provider access | Hugging Face (Standard), IBM watsonx.ai (Pay as you go) | Alibaba Cloud Model Studio (Standard), Openrouter (Standard) |
| Capabilities | embeddings | agents, chat, generation, reasoning, structured_outputs, tools, vision |
Granite Embedding 278m Multilingual Capabilities
Qwen3.7 Flash Capabilities
Related Comparisons
| A | Pair | B | Context |
|---|---|---|---|
| vs |  GPT-6 AstraOpenAI | cross-developer peers | |
Claude Fable 5.1Anthropic | vs | cross-developer peers | |
 Gemini 3.1 ProGoogle DeepMind | vs | cross-developer peers | |
 DeepSeek-V4.1-FlashDeepSeek | vs | cross-developer peers | |
| vs | Grok 4.6xAI | cross-developer peers | |
| vs | Qwen3.8-MaxQwen | cross-developer peers | |
| vs |  Kimi-K3Moonshot AI | cross-developer peersembedding | |
 MiniMax-M3MiniMax | vs | cross-developer peers | |
| vs |  GLM-5.3Z.ai | cross-developer peers | |
| vs |  Hy4 previewTencent | cross-developer peers | |
Seed 2.1 ProByteDance Seed | vs | cross-developer peers | |
| vs |  Mistral Large 3Mistral AI | cross-developer peers |
Primary Evidence
Sources and Freshness
Questions
Granite Embedding 278m Multilingual vs Qwen3.7 Flash FAQs
Is Granite Embedding 278m Multilingual or Qwen3.7 Flash better for coding?+
This comparison does not currently contain a protocol-matched coding benchmark for both Granite Embedding 278m Multilingual and Qwen3.7 Flash, so Model Markets cannot name a coding leader from pricing, context size, or capability labels alone.
Which is cheaper, Granite Embedding 278m Multilingual or Qwen3.7 Flash?+
Granite Embedding 278m Multilingual is $0.106 and Qwen3.7 Flash is $0.030 per million tokens, so Qwen3.7 Flash is cheaper on this metric. Only Qwen3.7 Flash has a directly sourced output price: $0.13 per million tokens.
Which has a larger context window, Granite Embedding 278m Multilingual or Qwen3.7 Flash?+
Qwen3.7 Flash has the larger sourced context window. Granite Embedding 278m Multilingual supports 1K and Qwen3.7 Flash supports 1,000K.
Which performs better in benchmarks, Granite Embedding 278m Multilingual or Qwen3.7 Flash?+
There is no overall benchmark winner: At least two independently verified, protocol-matched benchmarks are required for an overall winner.
Can Granite Embedding 278m Multilingual or Qwen3.7 Flash be self-hosted?+
Granite Embedding 278m Multilingual is the only model in this pair currently marked as self-hostable. Granite Embedding 278m Multilingual is open weight; Qwen3.7 Flash is not marked open weight.
Can Granite Embedding 278m Multilingual and Qwen3.7 Flash understand images?+
Granite Embedding 278m Multilingual is not documented with image input; Qwen3.7 Flash is documented with image input. This reflects supported input modalities, not vision quality.
Which can generate longer answers, Granite Embedding 278m Multilingual or Qwen3.7 Flash?+
Neither has a larger sourced maximum output. Granite Embedding 278m Multilingual is — and Qwen3.7 Flash is 66K.
Do Granite Embedding 278m Multilingual and Qwen3.7 Flash support reasoning and tool use?+
Granite Embedding 278m Multilingual: none of these features are definitively sourced. Qwen3.7 Flash: reasoning, tool calling, and image input. Feature support does not establish relative quality.
Which is available from more inference providers, Granite Embedding 278m Multilingual or Qwen3.7 Flash?+
Granite Embedding 278m Multilingual has 2 sourced provider routes; Qwen3.7 Flash has 2, a tie.
Which offers better value, Granite Embedding 278m Multilingual or Qwen3.7 Flash?+
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.