Agentic
Not comparable- Ling 3.0 Flash FP8
- Not measured
- Trinity-Large-Preview
- Not measured
- Weighted basis
- 0 vs 0 rows
- Reading
- Not comparable
Model comparison
Ling 3.0 Flash FP8 vs Trinity-Large-Preview
Updated August 4, 2026. Public scores include evidence status and uncertainty. They are not guarantees for a specific workload.
At least one model is not scored in the current public ranking lane, so the page does not name an overall quality winner.
1 results are shared. Category rows based on different benchmark sets are marked directional and do not name a winner.
Which one for your work
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.
Long documents
Prompts that approach the documented context limit
Trinity-Large-Preview
Trinity-Large-Preview has the larger documented context window.
Confidence: documented
Show secondary and unsupported calls
Coding work
Code generation, repair, and software-engineering tasks
Not enough matched evidence
No shared weighted benchmark basis supports a winner.
Confidence: limited
Agentic work
Tool use, computer use, and multi-step task completion
Not enough matched evidence
No shared weighted benchmark basis supports a winner.
Confidence: limited
Chat turn cost
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
Cache-heavy agent loop cost
200K cached + 20K fresh input + 10K output tokens
Not enough matched evidence
A complete comparable API-rate estimate is not available for both models.
Confidence: rate-fallback
Repository review cost
50K fresh input + 3K output tokens
Not enough matched evidence
A complete comparable API-rate estimate is not available for both models.
Confidence: listed-rates
What is actually comparable
Shared results can support a head-to-head reading. Results present for only one model describe coverage, not superiority.
3 Ling 3.0 Flash FP8 only
1 Shared
3 Trinity-Large-Preview only
- Shared results
- 1
- Ling 3.0 Flash FP8 only
- 3
- Trinity-Large-Preview only
- 3
- Like-for-like categories
- 0 / 8
Category results, on a stated basis
Each row states whether both averages use the same weighted benchmark set. Directional and not-comparable rows remain visible, but they never receive a winner in this template.
Coding
Not comparable- Ling 3.0 Flash FP8
- 40.4
- Trinity-Large-Preview
- Not measured
- Weighted basis
- 1 vs 0 rows
- Reading
- Not comparable
Reasoning
Not comparable- Ling 3.0 Flash FP8
- Not measured
- Trinity-Large-Preview
- Not measured
- Weighted basis
- 0 vs 0 rows
- Reading
- Not comparable
Knowledge
Not comparable- Ling 3.0 Flash FP8
- 84.0
- Trinity-Large-Preview
- Not measured
- Weighted basis
- 1 vs 0 rows
- Reading
- Not comparable
Math
Not comparable- Ling 3.0 Flash FP8
- Not measured
- Trinity-Large-Preview
- Not measured
- Weighted basis
- 0 vs 0 rows
- Reading
- Not comparable
Multilingual
Not comparable- Ling 3.0 Flash FP8
- Not measured
- Trinity-Large-Preview
- Not measured
- Weighted basis
- 0 vs 0 rows
- Reading
- Not comparable
Multimodal
Not comparable- Ling 3.0 Flash FP8
- Not measured
- Trinity-Large-Preview
- Not measured
- Weighted basis
- 0 vs 0 rows
- Reading
- Not comparable
Instruction following
Not comparable- Ling 3.0 Flash FP8
- 73.4
- Trinity-Large-Preview
- Not measured
- Weighted basis
- 1 vs 0 rows
- Reading
- Not comparable
| Category | Ling 3.0 Flash FP8 | Trinity-Large-Preview | Weighted basis | Reading |
|---|---|---|---|---|
| Agentic | Not measured | Not measured | Not comparable0 vs 0 rows | Not comparable |
| Coding | 40.4 | Not measured | Not comparable1 vs 0 rows | Not comparable |
| Reasoning | Not measured | Not measured | Not comparable0 vs 0 rows | Not comparable |
| Knowledge | 84.0 | Not measured | Not comparable1 vs 0 rows | Not comparable |
| Math | Not measured | Not measured | Not comparable0 vs 0 rows | Not comparable |
| Multilingual | Not measured | Not measured | Not comparable0 vs 0 rows | Not comparable |
| Multimodal | Not measured | Not measured | Not comparable0 vs 0 rows | Not comparable |
| Instruction following | 73.4 | Not measured | Not comparable1 vs 0 rows | Not comparable |
Shape of the matched evidence
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.
What each workload costs
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.
Chat turn
1K fresh input + 500 output tokens
- Ling 3.0 Flash FP8
- API rate not published
- Fits in one request
- Trinity-Large-Preview
- $0.00075
- Fits in one request
Ling 3.0 Flash FP8 has no comparable published API token rate.
Repository review
50K fresh input + 3K output tokens
- Ling 3.0 Flash FP8
- API rate not published
- Fits in one request
- Trinity-Large-Preview
- $0.0155
- Fits in one request
Ling 3.0 Flash FP8 has no comparable published API token rate.
Cache-heavy agent loop
200K cached + 20K fresh input + 10K output tokens
- Ling 3.0 Flash FP8
- API rate not published
- Fits in one request
- Cached-input rate unavailable
- Trinity-Large-Preview
- $0.065
- Fits in one request
- Cached input priced at the published list-input rate
Trinity-Large-Preview has no published cached-input rate, so cached tokens use its listed input rate. Ling 3.0 Flash FP8 has no comparable published API token rate.
Specification differences
Sourced differences are shown directly. Missing facts stay explicit instead of being inferred from a model name or family.
SpecificationLing 3.0 Flash FP8Trinity-Large-Preview
Context window
Maximum documented context; output-token limits may be lower.
Ling 3.0 Flash FP8
Trinity-Large-Preview
512K
API model ID
Ling 3.0 Flash FP8
Not sourced
Trinity-Large-Preview
Not sourced
Cached-input rate
A missing cached-input rate falls back to the listed input rate only in the stated workload estimate.
Ling 3.0 Flash FP8
No comparable hosted API rate
InclusionAI Ling 3.0 Flash FP8 model cardTrinity-Large-Preview
Not published
Documented inputs
Ling 3.0 Flash FP8
Not sourced
Trinity-Large-Preview
Not sourced
Documented outputs
Ling 3.0 Flash FP8
Not sourced
Trinity-Large-Preview
Not sourced
Provider availability
Ling 3.0 Flash FP8
Not sourced
Trinity-Large-Preview
Not sourced
Reasoning profile
Ling 3.0 Flash FP8
Reasoning
Trinity-Large-Preview
Non-Reasoning
Weight access
Ling 3.0 Flash FP8
Open Weight
Trinity-Large-Preview
Open Weight
License
Ling 3.0 Flash FP8
Open Weight
Trinity-Large-Preview
Open Weight
Release date
Ling 3.0 Flash FP8
2026-08-04
Trinity-Large-Preview
2026-01-27
If you already use one of these models
- Deployment change
- The models list different providers, so authentication, endpoint behavior, limits, and feature support may change.
- Quality signal
- At least one model is not scored in the current public ranking lane, so the page does not name an overall quality winner.
- Workload cost
- A complete comparable API-rate estimate is not available for both models.
- Context tradeoff
- Trinity-Large-Preview has the larger documented window (512K).
Run the same representative tasks against both endpoints before changing production traffic.
Benchmark evidence
The full public result ledger is available for audit without forcing a wide desktop table onto a phone.
Browse raw public benchmark evidence7 rows
Coding
SciCode
Ling 3.0 Flash FP840.4%SourceTrinity-Large-Preview—Not directly comparable
Knowledge
GPQA
Ling 3.0 Flash FP884%SourceTrinity-Large-Preview—Not directly comparable
GPQA-D
Ling 3.0 Flash FP884.0%SourceTrinity-Large-Preview63.3%SourceLing 3.0 Flash FP8 leads this result
MMLU
Ling 3.0 Flash FP8—Trinity-Large-Preview87.2%SourceNot directly comparable
MMLU-Pro (Arcee)
Ling 3.0 Flash FP8—Trinity-Large-Preview75.2%SourceNot directly comparable
Math
AIME25 (Arcee)
Ling 3.0 Flash FP8—Trinity-Large-Preview24.0%SourceNot directly comparable
Instruction following
IFBench
Ling 3.0 Flash FP873.4%SourceTrinity-Large-Preview—Not directly comparable
Frequently asked questions
Which is better, Ling 3.0 Flash FP8 or Trinity-Large-Preview?
At least one model is not scored in the current public ranking lane, so the page does not name an overall quality winner. The page therefore keeps the decision tied to the specific documented workload.
Which is better for coding, Ling 3.0 Flash FP8 or Trinity-Large-Preview?
The published evidence does not provide a shared weighted coding basis for both models, so BenchLM does not name a coding winner.
Which is better for agentic tasks, Ling 3.0 Flash FP8 or Trinity-Large-Preview?
The published evidence does not provide a shared weighted agentic tasks basis for both models, so BenchLM does not name a agentic tasks winner.
Which costs less, Ling 3.0 Flash FP8 or Trinity-Large-Preview?
Both models do not have comparable published API token rates, so this page does not name a universal price winner.
Which has the larger context window, Ling 3.0 Flash FP8 or Trinity-Large-Preview?
Trinity-Large-Preview has the larger documented context window: 512K, compared with 262K.
Related comparisons
Last updated August 4, 2026
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