Long documents
Prompts that approach the documented context limit
MiMo-V2-Omni
MiMo-V2-Omni has the larger documented context window.
Confidence: documented
MiMo-V2-Omni vs Step 3.7 Flash
Updated October 14, 2026. Rank says MiMo-V2-Omni is ahead. Price, access, and your workload can each overturn that. Public scores include evidence status and uncertainty.
Both of these models will change. Get the price, version and retirement notices for the pair, each with its source. Follow model changes
Share or export
Decision reading
MiMo-V2-Omni has the higher public point estimate, 49.98 versus 43.74. Their conditional score ranges overlap. These ranges do not establish rank confidence. 1 results are shared. Category rows resting on Estimated evidence or different benchmark sets are marked directional and do not name a winner.
- Shared results
- 1
- MiMo-V2-Omni only
- 1
- Step 3.7 Flash only
- 10
- Like-for-like categories
- 0 / 8
Estimated: MiMo-V2-Omni and Step 3.7 Flash. Conditional ranges do not establish rank confidence.How the comparison works
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.
Show secondary and unsupported calls
Coding work
Code generation, repair, and software-engineering tasks
Not enough matched evidence
MiMo-V2-Omni is not ranked on the public lane for coding, so no winner is named for coding.
Confidence: limitedAgentic work
Tool use, computer use, and multi-step task completion
Not enough matched evidence
MiMo-V2-Omni is not ranked on the public lane for agentic, so no winner is named for agentic.
Confidence: limitedChat 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-ratesCache-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-fallbackRepository 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
Which one for a specific job
Choose a job from the LLM Selector's task catalog to see the category row it rests on, under the same basis rules as the table below. A directional row stays directional; choosing a job never creates a winner.
The same task catalog as the LLM Selector. Each job names the evidence surface it rests on; nothing here adds a new score.
—MiMo-V2-Omni30.2Step 3.7 Flash
Not comparable · BenchAlign v5.8
The coding row is not comparable on the public lane: at least one model is not measured or not ranked there.
Coding scores combine specific tasks and setups. Match the editor, harness, and effort to your workflow.
Same basis rules as the category table below
What is actually comparable
Shared results can support a head-to-head reading. Results present for only one model describe coverage, not superiority.
1 MiMo-V2-Omni only
1 Shared
10 Step 3.7 Flash only
2 categories rest on Estimated evidence or different evidence sets. Those rows remain visible for coverage context but do not name a winner.
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.
Category results, on a stated basis
Each row shows the public-lane category score for both models: the BenchAlign v5.8 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.
Knowledge
Directional only- MiMo-V2-Omni
- 43.9
- Estimated · #100/181
- Step 3.7 Flash
- 45.0
- Estimated · #95/181
- Basis
- BenchAlign v5.8 lane · 0 vs 0 public rows
- Reading
- Directional only
Instruction following
Directional only- MiMo-V2-Omni
- 64.0
- #75/144
- Step 3.7 Flash
- 82.1
- #54/144
- Basis
- Provisional lane · 0 vs 0 weighted rows
- Reading
- Directional only
Agentic
Not comparable- MiMo-V2-Omni
- Not ranked
- Step 3.7 Flash
- 37.3
- Estimated · #73/125
- Basis
- BenchAlign v5.8 lane · 1 vs 7 public rows
- Reading
- Not comparable
Coding
Not comparable- MiMo-V2-Omni
- Not ranked
- Step 3.7 Flash
- 30.2
- Estimated · #95/149
- Basis
- BenchAlign v5.8 lane · 1 vs 2 public rows
- Reading
- Not comparable
Reasoning
Not comparable- MiMo-V2-Omni
- 77.4
- Unranked · 2 rankable rows
- Step 3.7 Flash
- 76.5
- Unranked · 2 rankable rows
- Basis
- Provisional lane · 0 vs 0 weighted rows
- Reading
- Not comparable
Multimodal
Not comparable- MiMo-V2-Omni
- 67.5
- Unranked · 1 rankable row
- Step 3.7 Flash
- 75.4
- Unranked · 3 rankable rows
- Basis
- Provisional lane · 0 vs 0 weighted rows
- Reading
- Not comparable
Multilingual
Not comparable- MiMo-V2-Omni
- Not ranked
- Step 3.7 Flash
- Not ranked
- Basis
- Provisional lane · 0 vs 0 weighted rows
- Reading
- Not comparable
Math
Not comparable- MiMo-V2-Omni
- Not ranked
- Step 3.7 Flash
- Not ranked
- Basis
- Provisional lane · 0 vs 0 weighted rows
- Reading
- Not comparable
| Category | MiMo-V2-Omni | Step 3.7 Flash | Basis | Reading |
|---|---|---|---|---|
| Knowledge | 43.9Estimated · #100/181 | 45.0Estimated · #95/181 | Directional onlyBenchAlign v5.8 lane · 0 vs 0 public rows | Directional only |
| Instruction following | 64.0#75/144 | 82.1#54/144 | Directional onlyProvisional lane · 0 vs 0 weighted rows | Directional only |
| Agentic | Not ranked | 37.3Estimated · #73/125 | Not comparableBenchAlign v5.8 lane · 1 vs 7 public rows | Not comparable |
| Coding | Not ranked | 30.2Estimated · #95/149 | Not comparableBenchAlign v5.8 lane · 1 vs 2 public rows | Not comparable |
| Reasoning | 77.4Unranked · 2 rankable rows | 76.5Unranked · 2 rankable rows | Not comparableProvisional lane · 0 vs 0 weighted rows | Not comparable |
| Multimodal | 67.5Unranked · 1 rankable row | 75.4Unranked · 3 rankable rows | 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 |
| Math | 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 v5.8) differ from the provisional-lane categories. Unranked scores sit on the provisional lane’s scale but never name a winner. Like-for-like rows within 0.5 points read as a practical tie.
Bars run 0–100Methodology
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-Omni
- API rate not published
- Fits in one request
- Step 3.7 Flash
- $0.00077
- Fits in one request
MiMo-V2-Omni has no comparable published API token rate.
Repository review
50K fresh input + 3K output tokens
- MiMo-V2-Omni
- API rate not published
- Fits in one request
- Step 3.7 Flash
- $0.01345
- Fits in one request
MiMo-V2-Omni has no comparable published API token rate.
Cache-heavy agent loop
200K cached + 20K fresh input + 10K output tokens
- MiMo-V2-Omni
- API rate not published
- Fits in one request
- Cached-input rate unavailable
- Step 3.7 Flash
- $0.0555
- Fits in one request
- Cached input priced at the published list-input rate
Step 3.7 Flash has no published cached-input rate, so cached tokens use its listed input rate. MiMo-V2-Omni has no comparable published API token rate.
Cached input falls back to the list input rate only where a cached rate is unpublished
Specification differences
Sourced differences are shown directly. Missing facts stay explicit instead of being inferred from a model name or family.
SpecificationMiMo-V2-OmniStep 3.7 Flash
Context window
Maximum documented context; output-token limits may be lower.
MiMo-V2-Omni
262K
Step 3.7 Flash
256K
API model ID
MiMo-V2-Omni
Not sourced
Step 3.7 Flash
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-Omni
No comparable hosted API rate
Step 3.7 Flash
Not published
Documented inputs
MiMo-V2-Omni
Not sourced
Step 3.7 Flash
Not sourced
Documented outputs
MiMo-V2-Omni
Not sourced
Step 3.7 Flash
Not sourced
Provider availability
MiMo-V2-Omni
Not sourced
Step 3.7 Flash
Not sourced
Reasoning profile
MiMo-V2-Omni
Reasoning
Step 3.7 Flash
Reasoning
Weight access
MiMo-V2-Omni
Proprietary
Step 3.7 Flash
Open Weight
License
MiMo-V2-Omni
Proprietary
Step 3.7 Flash
Open Weight
Release date
MiMo-V2-Omni
2026-03-18
Step 3.7 Flash
2026-05-29
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
- MiMo-V2-Omni has the higher public point estimate, 49.98 versus 43.74. Their conditional score ranges overlap. These ranges do not establish rank confidence.
- Workload cost
- A complete comparable API-rate estimate is not available for both models.
- Context tradeoff
- MiMo-V2-Omni has the larger documented window (262K).
Run the same representative tasks against both endpoints before changing production traffic.
Questions
Which is better, MiMo-V2-Omni or Step 3.7 Flash?
MiMo-V2-Omni has the higher public point estimate, 49.98 versus 43.74. Their conditional score ranges overlap. These ranges do not establish rank confidence. The page therefore keeps the decision tied to the specific documented workload.
Which is better for coding, MiMo-V2-Omni or Step 3.7 Flash?
MiMo-V2-Omni is not ranked on the public lane for coding, so no winner is named for coding.
Which is better for agentic tasks, MiMo-V2-Omni or Step 3.7 Flash?
MiMo-V2-Omni is not ranked on the public lane for agentic tasks, so no winner is named for agentic tasks.
Which costs less, MiMo-V2-Omni or Step 3.7 Flash?
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-Omni or Step 3.7 Flash?
MiMo-V2-Omni has the larger documented context window: 262K, compared with 256K.
Benchmark evidence
The full public result ledger is available for audit without forcing a wide desktop table onto a phone.
Browse raw public benchmark evidence12 rows
Agentic
Claw-Eval
MiMo-V2-Omni45.2%SourceStep 3.7 Flash67.1%SourceStep 3.7 Flash leads this result
Terminal-Bench 2.1
MiMo-V2-Omni—Step 3.7 Flash59.5%SourceNot directly comparable
BrowseComp
MiMo-V2-Omni—Step 3.7 Flash75.8%SourceNot directly comparable
DeepSearchQA
MiMo-V2-Omni—Step 3.7 Flash92.8%SourceNot directly comparable
Toolathlon
MiMo-V2-Omni—Step 3.7 Flash49.5%SourceNot directly comparable
HLE w/ tools
MiMo-V2-Omni—Step 3.7 Flash47.2%SourceNot directly comparable
Gert Labs
MiMo-V2-Omni—Step 3.7 Flash51.57%SourceNot directly comparable
Coding
Multimodal
12 public results · 1 shared
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Last updated October 14, 2026