Knowledge
Directional only- Interfaze Beta
- 51.1
- Estimated · #85/181
- Mellum2-12B-A2.5B-Instruct
- 48.1
- Estimated · #103/181
- Basis
- BenchAlign lane · 3 vs 3 public rows
- Reading
- Directional only
Interfaze Beta vs Mellum2-12B-A2.5B-Instruct
Updated September 4, 2026. Public scores include evidence status and uncertainty. They are not guarantees for a specific workload.
Decision reading
At least one model is not scored in the current public ranking lane, so the page does not name an overall quality winner.
2 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
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
Interfaze Beta
Interfaze Beta 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
Interfaze Beta and Mellum2-12B-A2.5B-Instruct are not ranked on the public lane for coding, so no winner is named for coding.
Confidence: limited
Agentic work
Tool use, computer use, and multi-step task completion
Not enough matched evidence
Interfaze Beta is not ranked on the public lane for agentic, so no winner is named for agentic.
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
The page does not recommend a cost winner because at least one model cannot fit the stated workload in one request. Mellum2-12B-A2.5B-Instruct does not fit this workload in one request. Interfaze Beta has no published cached-input rate, so cached tokens use its listed input rate. Mellum2-12B-A2.5B-Instruct has no comparable published API token rate.
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.
7 Interfaze Beta only
2 Shared
4 Mellum2-12B-A2.5B-Instruct only
- Shared results
- 2
- Interfaze Beta only
- 7
- Mellum2-12B-A2.5B-Instruct only
- 4
- Like-for-like categories
- 0 / 8
1 category rests on Estimated evidence or different evidence sets. Those rows remain visible for coverage context but do not name a winner.
Category results, on a stated basis
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.
Agentic
Not comparable- Interfaze Beta
- Not ranked
- Mellum2-12B-A2.5B-Instruct
- 47.8
- Estimated · #82/151
- Basis
- BenchAlign lane · 0 vs 1 public rows
- Reading
- Not comparable
Coding
Not comparable- Interfaze Beta
- Not ranked
- Mellum2-12B-A2.5B-Instruct
- Not ranked
- Basis
- BenchAlign lane · 1 vs 1 public rows
- Reading
- Not comparable
Reasoning
Not comparable- Interfaze Beta
- Not ranked
- Mellum2-12B-A2.5B-Instruct
- Not ranked
- Basis
- Provisional lane · 0 vs 0 weighted rows
- Reading
- Not comparable
Math
Not comparable- Interfaze Beta
- Not ranked
- Mellum2-12B-A2.5B-Instruct
- Not ranked
- Basis
- Provisional lane · 0 vs 0 weighted rows
- Reading
- Not comparable
Multilingual
Not comparable- Interfaze Beta
- Not ranked
- Mellum2-12B-A2.5B-Instruct
- Not ranked
- Basis
- Provisional lane · 0 vs 0 weighted rows
- Reading
- Not comparable
Multimodal
Not comparable- Interfaze Beta
- 27.5
- Unranked · 5 rankable rows
- Mellum2-12B-A2.5B-Instruct
- Not ranked
- Basis
- Provisional lane · 1 vs 0 weighted rows
- Reading
- Not comparable
Instruction following
Not comparable- Interfaze Beta
- Not ranked
- Mellum2-12B-A2.5B-Instruct
- Not ranked
- Basis
- Provisional lane · 0 vs 0 weighted rows
- Reading
- Not comparable
| Category | Interfaze Beta | Mellum2-12B-A2.5B-Instruct | Basis | Reading |
|---|---|---|---|---|
| Knowledge | 51.1Estimated · #85/181 | 48.1Estimated · #103/181 | Directional onlyBenchAlign lane · 3 vs 3 public rows | Directional only |
| Agentic | Not ranked | 47.8Estimated · #82/151 | Not comparableBenchAlign lane · 0 vs 1 public rows | Not comparable |
| Coding | Not ranked | Not ranked | Not comparableBenchAlign lane · 1 vs 1 public rows | Not comparable |
| Reasoning | Not ranked | Not ranked | Not comparableProvisional lane · 0 vs 0 weighted 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 | 27.5Unranked · 5 rankable rows | Not ranked | Not comparableProvisional lane · 1 vs 0 weighted rows | Not comparable |
| Instruction following | Not ranked | 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.
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.
Too few matched category axes support a radar. The ruled list below shows only shared benchmark results; positions use each benchmark’s normalized display scale when available.
GPQA
Knowledge
Interfaze Beta: 89.9%Mellum2-12B-A2.5B-Instruct: 40.9%Normalized gap 49.0Interfaze Beta source Mellum2-12B-A2.5B-Instruct source
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
- Interfaze Beta
- $0.00325
- Fits in one request
- Mellum2-12B-A2.5B-Instruct
- API rate not published
- Fits in one request
Mellum2-12B-A2.5B-Instruct has no comparable published API token rate.
Repository review
50K fresh input + 3K output tokens
- Interfaze Beta
- $0.0855
- Fits in one request
- Mellum2-12B-A2.5B-Instruct
- API rate not published
- Fits in one request
Mellum2-12B-A2.5B-Instruct has no comparable published API token rate.
Cache-heavy agent loop
200K cached + 20K fresh input + 10K output tokens
- Interfaze Beta
- $0.365
- Fits in one request
- Cached input priced at the published list-input rate
- Mellum2-12B-A2.5B-Instruct
- API rate not published
- Does not fit in one request
- Cached-input rate unavailable
Mellum2-12B-A2.5B-Instruct does not fit this workload in one request. Interfaze Beta has no published cached-input rate, so cached tokens use its listed input rate. Mellum2-12B-A2.5B-Instruct 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.
SpecificationInterfaze BetaMellum2-12B-A2.5B-Instruct
Context window
Maximum documented context; output-token limits may be lower.
Interfaze Beta
1M
Mellum2-12B-A2.5B-Instruct
128K
API model ID
Interfaze Beta
Not sourced
Mellum2-12B-A2.5B-Instruct
Not sourced
Cached-input rate
A missing cached-input rate falls back to the listed input rate only in the stated workload estimate.
Interfaze Beta
Not published
Mellum2-12B-A2.5B-Instruct
No comparable hosted API rate
Documented inputs
Interfaze Beta
Not sourced
Mellum2-12B-A2.5B-Instruct
Not sourced
Documented outputs
Interfaze Beta
Not sourced
Mellum2-12B-A2.5B-Instruct
Not sourced
Provider availability
Interfaze Beta
Not sourced
Mellum2-12B-A2.5B-Instruct
Not sourced
Reasoning profile
Interfaze Beta
Reasoning
Mellum2-12B-A2.5B-Instruct
Non-Reasoning
Weight access
Interfaze Beta
Proprietary
Mellum2-12B-A2.5B-Instruct
Open Weight
License
Interfaze Beta
Proprietary
Mellum2-12B-A2.5B-Instruct
Open Weight
Release date
Interfaze Beta
2026-05-11
Mellum2-12B-A2.5B-Instruct
2026-05-28
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
- Interfaze Beta has the larger documented window (1M).
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 evidence13 rows
Agentic
BFCL v4
Interfaze Beta—Mellum2-12B-A2.5B-Instruct44.2%SourceNot directly comparable
Coding
Knowledge
GPQA
Interfaze Beta89.9%SourceMellum2-12B-A2.5B-Instruct40.9%SourceInterfaze Beta leads this result
GPQA-D
Interfaze Beta89.9%SourceMellum2-12B-A2.5B-Instruct40.9%SourceInterfaze Beta leads this result
MMMLU
Interfaze Beta90.9%SourceMellum2-12B-A2.5B-Instruct—Not directly comparable
MMLU-Redux
Interfaze Beta—Mellum2-12B-A2.5B-Instruct78.1%SourceNot directly comparable
Multimodal
OCRBench V2
Interfaze Beta70.7%SourceMellum2-12B-A2.5B-Instruct—Not directly comparable
olmOCR
Interfaze Beta85.7%SourceMellum2-12B-A2.5B-Instruct—Not directly comparable
RefCOCO (avg)
Interfaze Beta82.1%SourceMellum2-12B-A2.5B-Instruct—Not directly comparable
MMMU-Pro
Interfaze Beta71.1%SourceMellum2-12B-A2.5B-Instruct—Not directly comparable
Instruction following
Frequently asked questions
Which is better, Interfaze Beta or Mellum2-12B-A2.5B-Instruct?
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, Interfaze Beta or Mellum2-12B-A2.5B-Instruct?
Interfaze Beta and Mellum2-12B-A2.5B-Instruct are not ranked on the public lane for coding, so no winner is named for coding.
Which is better for agentic tasks, Interfaze Beta or Mellum2-12B-A2.5B-Instruct?
Interfaze Beta is not ranked on the public lane for agentic tasks, so no winner is named for agentic tasks.
Which costs less, Interfaze Beta or Mellum2-12B-A2.5B-Instruct?
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, Interfaze Beta or Mellum2-12B-A2.5B-Instruct?
Interfaze Beta has the larger documented context window: 1M, compared with 128K.
Related comparisons
Last updated September 4, 2026
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