Agentic
Not comparable- Granite-4.0-H-350M
- Not ranked
- Trinity-Large-Preview
- Not ranked
- Basis
- BenchAlign lane · 0 vs 0 public rows
- Reading
- Not comparable
Five or fewer confirmed AI changes, with original sources, on mornings when something changed.A free source-linked morning brief.
See the free Radar BriefUpdated September 4, 2026. Public scores include evidence status and uncertainty. They are not guarantees for a specific workload.
Decision reading
The public evidence has no benchmark result shared by both models, so it does not support a quality verdict. Use the documented cost, context, and runtime rows instead.
0 results are shared. Category rows resting on Estimated evidence or different benchmark sets are marked directional and do not name a winner.
Share or export
Recommendations appear only when a shared evidence basis or an explicit operating constraint supports the call. Secondary and unsupported use cases stay disclosed below the initial list.
Prompts that approach the documented context limit
Trinity-Large-Preview
Trinity-Large-Preview has the larger documented context window.
Confidence: documented
Code generation, repair, and software-engineering tasks
Not enough matched evidence
Trinity-Large-Preview is not ranked on the public lane for coding, so no winner is named for coding.
Confidence: limited
Tool use, computer use, and multi-step task completion
Not enough matched evidence
Granite-4.0-H-350M and Trinity-Large-Preview are not ranked on the public lane for agentic, so no winner is named for agentic.
Confidence: limited
1K fresh input + 500 output tokens
Not enough matched evidence
A complete comparable API-rate estimate is not available for both models.
Confidence: listed-rates
200K cached + 20K fresh input + 10K output tokens
Not enough matched evidence
The page does not recommend a cost winner because at least one model cannot fit the stated workload in one request. Granite-4.0-H-350M does not fit this workload in one request. Trinity-Large-Preview has no published cached-input rate, so cached tokens use its listed input rate. Granite-4.0-H-350M has no comparable published API token rate.
Confidence: rate-fallback
50K fresh input + 3K output tokens
Not enough matched evidence
The page does not recommend a cost winner because at least one model cannot fit the stated workload in one request. Granite-4.0-H-350M does not fit this workload in one request. Granite-4.0-H-350M has no comparable published API token rate.
Confidence: listed-rates
Shared results can support a head-to-head reading. Results present for only one model describe coverage, not superiority.
Each row shows the public-lane category score for both models: the BenchAlign lane for agentic, coding, and knowledge, and the weighted public rows elsewhere, with the same rank each model page reports. A row is like-for-like only when both scores rest on Supported evidence or the same weighted set. Directional and not-comparable rows remain visible, but they never receive a winner.
| Category | Granite-4.0-H-350M | Trinity-Large-Preview | Basis | Reading |
|---|---|---|---|---|
| Agentic | Not ranked | Not ranked | Not comparableBenchAlign lane · 0 vs 0 public rows | Not comparable |
| Coding | 43.6Estimated · #122/183 | Not ranked | Not comparableBenchAlign lane · 0 vs 0 public rows | Not comparable |
| Reasoning | 21.0Unranked · 2 rankable rows | Not ranked | Not comparableProvisional lane · 0 vs 0 weighted rows | Not comparable |
| Knowledge | 35.3Estimated · #162/181 | Not ranked | Not comparableBenchAlign lane · 0 vs 3 public rows | Not comparable |
| Math | Not ranked | Not ranked | Not comparableProvisional lane · 0 vs 0 weighted rows | Not comparable |
| Multilingual | Not ranked | Not ranked | Not comparableProvisional lane · 0 vs 0 weighted rows | Not comparable |
| Multimodal | Not ranked | Not ranked | Not comparableProvisional lane · 0 vs 0 weighted rows | Not comparable |
| Instruction following | 28.5#117/120 | Not ranked | Not comparableProvisional lane · 0 vs 0 weighted rows | Not comparable |
Ranks count the models scored in each category’s lane, so the agentic, coding, and knowledge denominators (BenchAlign) differ from the provisional-lane categories. Unranked scores sit on the lane’s scale but never name a winner. Like-for-like rows within 0.5 points read as a practical tie.
Only shared public evidence is shown. Sparse evidence stays a ruled list rather than being closed into a radar shape.
A shared-evidence shape is not available.
BenchLM does not draw a radar or infer missing axes when the matched evidence is too sparse.
Three fixed token mixes turn per-token rates into comparable decisions. Each scenario states context fit and whether cached input had to fall back to the published list-input rate.
1K fresh input + 500 output tokens
Granite-4.0-H-350M has no comparable published API token rate.
50K fresh input + 3K output tokens
Granite-4.0-H-350M does not fit this workload in one request. Granite-4.0-H-350M has no comparable published API token rate.
200K cached + 20K fresh input + 10K output tokens
Granite-4.0-H-350M does not fit this workload in one request. Trinity-Large-Preview has no published cached-input rate, so cached tokens use its listed input rate. Granite-4.0-H-350M has no comparable published API token rate.
Sourced differences are shown directly. Missing facts stay explicit instead of being inferred from a model name or family.
Maximum documented context; output-token limits may be lower.
Granite-4.0-H-350M
32K
Trinity-Large-Preview
512K
Granite-4.0-H-350M
Not sourced
Trinity-Large-Preview
Not sourced
A missing cached-input rate falls back to the listed input rate only in the stated workload estimate.
Granite-4.0-H-350M
No comparable hosted API rate
Trinity-Large-Preview
Not published
Granite-4.0-H-350M
Not sourced
Trinity-Large-Preview
Not sourced
Granite-4.0-H-350M
Not sourced
Trinity-Large-Preview
Not sourced
Granite-4.0-H-350M
Not sourced
Trinity-Large-Preview
Not sourced
Granite-4.0-H-350M
Non-Reasoning
Trinity-Large-Preview
Non-Reasoning
Granite-4.0-H-350M
Open Weight
Trinity-Large-Preview
Open Weight
Granite-4.0-H-350M
Open Weight
Trinity-Large-Preview
Open Weight
Granite-4.0-H-350M
2025-10-28
Trinity-Large-Preview
2026-01-27
Run the same representative tasks against both endpoints before changing production traffic.
The full public result ledger is available for audit without forcing a wide desktop table onto a phone.
AIME25 (Arcee)
Not directly comparable
The public evidence has no benchmark result shared by both models, so it does not support a quality verdict. The page therefore keeps the decision tied to the specific documented workload.
Trinity-Large-Preview is not ranked on the public lane for coding, so no winner is named for coding.
Granite-4.0-H-350M and Trinity-Large-Preview are not ranked on the public lane for agentic tasks, so no winner is named for agentic tasks.
Both models do not have comparable published API token rates, so this page does not name a universal price winner.
Trinity-Large-Preview has the larger documented context window: 512K, compared with 32K.
Last updated September 4, 2026
One weekly email when material rank, price, or benchmark evidence changes make this matchup worth revisiting.
Read a sample issueJoin 2,000+ readers.