Agentic
Like-for-like- MiMo-V2.5-Pro
- 68.4
- Ornith-1.0-397B
- 77.5
- Weighted basis
- 1 vs 1 rows
- Reading
- Ornith-1.0-397B leads
MiMo-V2.5-Pro vs Ornith-1.0-397B
Updated August 13, 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.
4 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.
Agentic work
Tool use, computer use, and multi-step task completion
Ornith-1.0-397B
Ornith-1.0-397B leads on the same 1 weighted benchmark row.
Confidence: limited
Long documents
Prompts that approach the documented context limit
MiMo-V2.5-Pro
MiMo-V2.5-Pro 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
The category averages use different weighted benchmark sets, so they are directional rather than like-for-like.
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: listed-rates
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.
4 MiMo-V2.5-Pro only
4 Shared
3 Ornith-1.0-397B only
- Shared results
- 4
- MiMo-V2.5-Pro only
- 4
- Ornith-1.0-397B only
- 3
- Like-for-like categories
- 1 / 8
1 category uses different evidence sets. Those rows remain visible for coverage context but do not name a winner.
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
Directional only- MiMo-V2.5-Pro
- 57.2
- Ornith-1.0-397B
- 74.6
- Weighted basis
- 1 vs 2 rows
- Reading
- Directional only
Reasoning
Not comparable- MiMo-V2.5-Pro
- Not measured
- Ornith-1.0-397B
- Not measured
- Weighted basis
- 0 vs 0 rows
- Reading
- Not comparable
Knowledge
Not comparable- MiMo-V2.5-Pro
- 48.0
- Ornith-1.0-397B
- Not measured
- Weighted basis
- 1 vs 0 rows
- Reading
- Not comparable
Math
Not comparable- MiMo-V2.5-Pro
- Not measured
- Ornith-1.0-397B
- Not measured
- Weighted basis
- 0 vs 0 rows
- Reading
- Not comparable
Multilingual
Not comparable- MiMo-V2.5-Pro
- Not measured
- Ornith-1.0-397B
- Not measured
- Weighted basis
- 0 vs 0 rows
- Reading
- Not comparable
Multimodal
Not comparable- MiMo-V2.5-Pro
- Not measured
- Ornith-1.0-397B
- Not measured
- Weighted basis
- 0 vs 0 rows
- Reading
- Not comparable
Instruction following
Not comparable- MiMo-V2.5-Pro
- Not measured
- Ornith-1.0-397B
- Not measured
- Weighted basis
- 0 vs 0 rows
- Reading
- Not comparable
| Category | MiMo-V2.5-Pro | Ornith-1.0-397B | Weighted basis | Reading |
|---|---|---|---|---|
| Agentic | 68.4 | 77.5 | Like-for-like1 vs 1 rows | Ornith-1.0-397B leads |
| Coding | 57.2 | 74.6 | Directional only1 vs 2 rows | Directional only |
| Reasoning | Not measured | Not measured | Not comparable0 vs 0 rows | Not comparable |
| Knowledge | 48.0 | 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 | Not measured | Not measured | Not comparable0 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.
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.
Terminal-Bench 2.0
Agentic
MiMo-V2.5-Pro: 68.4%Ornith-1.0-397B: 77.5%Normalized gap 9.1MiMo-V2.5-Pro source Ornith-1.0-397B sourceSWE-bench Pro
Coding
MiMo-V2.5-Pro: 57.2%Ornith-1.0-397B: 62.2%Normalized gap 5.0MiMo-V2.5-Pro source Ornith-1.0-397B 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
- MiMo-V2.5-Pro
- API rate not published
- Fits in one request
- Ornith-1.0-397B
- Self-hosted; infrastructure cost varies
- Fits in one request
MiMo-V2.5-Pro has no comparable published API token rate. Ornith-1.0-397B has no comparable published API token rate.
Repository review
50K fresh input + 3K output tokens
- MiMo-V2.5-Pro
- API rate not published
- Fits in one request
- Ornith-1.0-397B
- Self-hosted; infrastructure cost varies
- Fits in one request
MiMo-V2.5-Pro has no comparable published API token rate. Ornith-1.0-397B has no comparable published API token rate.
Cache-heavy agent loop
200K cached + 20K fresh input + 10K output tokens
- MiMo-V2.5-Pro
- API rate not published
- Fits in one request
- Cached-input rate unavailable
- Ornith-1.0-397B
- Self-hosted; infrastructure cost varies
- Fits in one request
- Cached-input rate unavailable
MiMo-V2.5-Pro has no comparable published API token rate. Ornith-1.0-397B 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.
SpecificationMiMo-V2.5-ProOrnith-1.0-397B
Context window
Maximum documented context; output-token limits may be lower.
MiMo-V2.5-Pro
1M
Ornith-1.0-397B
256K
API model ID
MiMo-V2.5-Pro
Not sourced
Ornith-1.0-397B
Not sourced
Cached-input rate
A missing cached-input rate falls back to the listed input rate only in the stated workload estimate.
MiMo-V2.5-Pro
No comparable hosted API rate
Ornith-1.0-397B
No comparable hosted API rate
Documented inputs
MiMo-V2.5-Pro
Not sourced
Ornith-1.0-397B
Not sourced
Documented outputs
MiMo-V2.5-Pro
Not sourced
Ornith-1.0-397B
Not sourced
Provider availability
MiMo-V2.5-Pro
Not sourced
Ornith-1.0-397B
Not sourced
Reasoning profile
MiMo-V2.5-Pro
Reasoning
Ornith-1.0-397B
Reasoning
Weight access
MiMo-V2.5-Pro
Proprietary
Ornith-1.0-397B
Open Weight
License
MiMo-V2.5-Pro
Proprietary
Ornith-1.0-397B
Open Weight
Release date
MiMo-V2.5-Pro
2026-04-22
Ornith-1.0-397B
2026-06-01
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
- MiMo-V2.5-Pro 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 evidence11 rows
Agentic
Claw-Eval
MiMo-V2.5-Pro63.8%SourceOrnith-1.0-397B77.1%SourceOrnith-1.0-397B leads this result
τ³-bench results
MiMo-V2.5-Pro72.9%SourceOrnith-1.0-397B—Not directly comparable
Terminal-Bench 2.0
MiMo-V2.5-Pro68.4%SourceOrnith-1.0-397B77.5%SourceOrnith-1.0-397B leads this result
Gert Labs
MiMo-V2.5-Pro62.70%SourceOrnith-1.0-397B—Not directly comparable
Coding
SWE-bench Pro
MiMo-V2.5-Pro57.2%SourceOrnith-1.0-397B62.2%SourceOrnith-1.0-397B leads this result
Terminal-Bench 2.0
MiMo-V2.5-Pro68.4%SourceOrnith-1.0-397B77.5%SourceOrnith-1.0-397B leads this result
SWE-bench Verified
MiMo-V2.5-Pro—Ornith-1.0-397B82.4%SourceNot directly comparable
SWE Multilingual
MiMo-V2.5-Pro—Ornith-1.0-397B78.9%SourceNot directly comparable
NL2Repo
MiMo-V2.5-Pro—Ornith-1.0-397B48.2%SourceNot directly comparable
Knowledge
Frequently asked questions
Which is better, MiMo-V2.5-Pro or Ornith-1.0-397B?
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, MiMo-V2.5-Pro or Ornith-1.0-397B?
The current coding averages use different weighted benchmark sets, so BenchLM does not name a winner from them. Read the shared benchmark rows directly and test the models on the same task set.
Which is better for agentic tasks, MiMo-V2.5-Pro or Ornith-1.0-397B?
Ornith-1.0-397B leads the like-for-like agentic tasks comparison across 1 shared weighted benchmark row.
Which costs less, MiMo-V2.5-Pro or Ornith-1.0-397B?
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, MiMo-V2.5-Pro or Ornith-1.0-397B?
MiMo-V2.5-Pro has the larger documented context window: 1M, compared with 256K.
Related comparisons
Last updated August 13, 2026
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