Model comparison
Granite-4.0-H-1B vs Ling 3.0 Flash
Head-to-head evidence from 0 shared benchmark results across 0 categories. Overall scores shown here use the public BenchAlign v5 ranking lane.
Evidence parity. Granite-4.0-H-1B and Ling 3.0 Flash share 0 comparable benchmark results. 0 of 8 categories are comparable. 11 results are unique to Granite-4.0-H-1B; 0 to Ling 3.0 Flash.
Updated July 24, 2026- Shared results
- 0
- Granite-4.0-H-1B only
- 11
- Ling 3.0 Flash only
- 0
- Comparable categories
- 0 / 8
Benchmark data for Granite-4.0-H-1B and Ling 3.0 Flash is coming soon on BenchLM.
Confidence note. This is a partial-evidence comparison with 0 shared benchmark results across 0 evidence categories; 0 of 8 categories currently have scoreable aggregates for both models. Treat the verdict as directional until coverage is more balanced.
Why this result
BenchLM does not have sourced benchmark coverage for Ling 3.0 Flash yet. This comparison is currently limited to metadata such as context window, reasoning mode, and pricing where available.
Ling 3.0 Flash has the larger context window at 262K, compared with 128K for Granite-4.0-H-1B.
Operational comparison
Runtime and commercial metrics are compared only when both models have a complete sourced value.
| Metric | Granite-4.0-H-1B | Ling 3.0 Flash | Comparison |
|---|---|---|---|
| Input / output priceUSD per 1M tokens | Granite-4.0-H-1B$0 input / $0 output | Ling 3.0 FlashNot available | A complete price comparison is not available. |
| Generation speedtokens per second | Granite-4.0-H-1BNot available | Ling 3.0 FlashNot available | A complete speed comparison is not available. |
| First-answer latencyseconds to first token | Granite-4.0-H-1BNot available | Ling 3.0 FlashNot available | A complete latency comparison is not available. |
| Context windowmaximum listed tokens | Granite-4.0-H-1B128K | Ling 3.0 Flash262K | Ling 3.0 Flash lists the larger context window. |
Benchmark Deep Dive
Agentic1 benchmarks
| Benchmark | Granite-4.0-H-1B | Ling 3.0 Flash | Result |
|---|---|---|---|
| τ²-bench resultsSource | 19.6% | — | Not comparable |
Coding1 benchmarks
| Benchmark | Granite-4.0-H-1B | Ling 3.0 Flash | Result |
|---|---|---|---|
| AA-SciCodeSource | 8.2% | — | Not comparable |
Reasoning2 benchmarks
Knowledge6 benchmarks
| Benchmark | Granite-4.0-H-1B | Ling 3.0 Flash | Result |
|---|---|---|---|
| Artificial Analysis Intelligence IndexSource | 2.7% | — | Not comparable |
| AA-GPQA DiamondSource | 24.6% | — | Not comparable |
| AA-HLESource | 5.0% | — | Not comparable |
| AA-Omniscience IndexSource | -73.6% | — | Not comparable |
| AA-Omniscience AccuracySource | 5.3% | — | Not comparable |
| AA-Omniscience Hallucination RateSource | 83.4% | — | Not comparable |
Inst. Following1 benchmarks
| Benchmark | Granite-4.0-H-1B | Ling 3.0 Flash | Result |
|---|---|---|---|
| AA-IFBenchSource | 25.1% | — | Not comparable |
Frequently Asked Questions (3)
Can I compare Granite-4.0-H-1B and Ling 3.0 Flash on BenchLM yet?
Not fully yet. BenchLM is tracking both models, but the sourced benchmark breakdown for this comparison is still coming soon.
Why does this comparison show “coming soon”?
BenchLM only shows category winners and benchmark-level calls when we have sourced results that can be compared fairly. For these models, the public benchmark coverage is not complete enough yet.
What data is available for Granite-4.0-H-1B and Ling 3.0 Flash today?
Granite-4.0-H-1B: $0.00 input / $0.00 output per 1M tokens Ling 3.0 Flash: Pricing unavailable Both model pages still include creator, context window, reasoning mode, and other metadata while benchmark coverage fills in.