Coding
Like-for-like- GPT-5.6 Sol
- 64.6
- MiMo-V2.5
- 56.1
- Weighted basis
- 1 vs 1 rows
- Reading
- GPT-5.6 Sol leads
Model comparison
GPT-5.6 Sol vs MiMo-V2.5
Updated August 10, 2026. Public scores include evidence status and uncertainty. They are not guarantees for a specific workload.
GPT-5.6 Sol has the higher public score, 81.48 versus 57.92, and the 90% score intervals do not overlap.
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.
Coding work
Code generation, repair, and software-engineering tasks
GPT-5.6 Sol
GPT-5.6 Sol leads on the same 1 weighted benchmark row.
Confidence: limited
Long documents
Prompts that approach the documented context limit
GPT-5.6 Sol
GPT-5.6 Sol has the larger documented context window.
Confidence: documented
Show secondary and unsupported calls
Agentic work
Tool use, computer use, and multi-step task completion
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.
20 GPT-5.6 Sol only
4 Shared
6 MiMo-V2.5 only
- Shared results
- 4
- GPT-5.6 Sol only
- 20
- MiMo-V2.5 only
- 6
- Like-for-like categories
- 1 / 8
2 categories use 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.
Agentic
Directional only- GPT-5.6 Sol
- 92.0
- MiMo-V2.5
- 65.8
- Weighted basis
- 2 vs 1 rows
- Reading
- Directional only
Multimodal
Directional only- GPT-5.6 Sol
- 83.0
- MiMo-V2.5
- 79.0
- Weighted basis
- 1 vs 2 rows
- Reading
- Directional only
Reasoning
Not comparable- GPT-5.6 Sol
- 92.5
- MiMo-V2.5
- Not measured
- Weighted basis
- 1 vs 0 rows
- Reading
- Not comparable
Knowledge
Not comparable- GPT-5.6 Sol
- 94.6
- MiMo-V2.5
- Not measured
- Weighted basis
- 1 vs 0 rows
- Reading
- Not comparable
Math
Not comparable- GPT-5.6 Sol
- 87.5
- MiMo-V2.5
- Not measured
- Weighted basis
- 2 vs 0 rows
- Reading
- Not comparable
Multilingual
Not comparable- GPT-5.6 Sol
- Not measured
- MiMo-V2.5
- Not measured
- Weighted basis
- 0 vs 0 rows
- Reading
- Not comparable
Instruction following
Not comparable- GPT-5.6 Sol
- Not measured
- MiMo-V2.5
- Not measured
- Weighted basis
- 0 vs 0 rows
- Reading
- Not comparable
| Category | GPT-5.6 Sol | MiMo-V2.5 | Weighted basis | Reading |
|---|---|---|---|---|
| Coding | 64.6 | 56.1 | Like-for-like1 vs 1 rows | GPT-5.6 Sol leads |
| Agentic | 92.0 | 65.8 | Directional only2 vs 1 rows | Directional only |
| Multimodal | 83.0 | 79.0 | Directional only1 vs 2 rows | Directional only |
| Reasoning | 92.5 | Not measured | Not comparable1 vs 0 rows | Not comparable |
| Knowledge | 94.6 | Not measured | Not comparable1 vs 0 rows | Not comparable |
| Math | 87.5 | Not measured | Not comparable2 vs 0 rows | Not comparable |
| Multilingual | 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
SWE-bench Pro
Coding
MMMU-Pro
Multimodal
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
- GPT-5.6 Sol
- $0.02
- Fits in one request
- MiMo-V2.5
- API rate not published
- Fits in one request
MiMo-V2.5 has no comparable published API token rate.
Repository review
50K fresh input + 3K output tokens
- GPT-5.6 Sol
- $0.34
- Fits in one request
- MiMo-V2.5
- API rate not published
- Fits in one request
MiMo-V2.5 has no comparable published API token rate.
Cache-heavy agent loop
200K cached + 20K fresh input + 10K output tokens
- GPT-5.6 Sol
- $0.5
- Fits in one request
- MiMo-V2.5
- API rate not published
- Fits in one request
- Cached-input rate unavailable
MiMo-V2.5 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.
SpecificationGPT-5.6 SolMiMo-V2.5
Context window
Maximum documented context; output-token limits may be lower.
GPT-5.6 Sol
1.05M
OpenAI model catalogMiMo-V2.5
1M
API model ID
GPT-5.6 Sol
gpt-5.6-sol
OpenAI model catalogMiMo-V2.5
Not sourced
Cached-input rate
A missing cached-input rate falls back to the listed input rate only in the stated workload estimate.
GPT-5.6 Sol
$0.5 per 1M cached input tokens
OpenAI pricingMiMo-V2.5
No comparable hosted API rate
Documented inputs
GPT-5.6 Sol
text, image
OpenAI model catalogMiMo-V2.5
Not sourced
Documented outputs
GPT-5.6 Sol
MiMo-V2.5
Not sourced
Provider availability
GPT-5.6 Sol
Generally Available · OpenAI Responses API
OpenAI model catalogMiMo-V2.5
Not sourced
Reasoning profile
GPT-5.6 Sol
Reasoning
MiMo-V2.5
Reasoning
Weight access
GPT-5.6 Sol
Proprietary
MiMo-V2.5
Proprietary
License
GPT-5.6 Sol
Proprietary
MiMo-V2.5
Proprietary
Release date
GPT-5.6 Sol
2026-07-09
MiMo-V2.5
2026-04-22
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
- GPT-5.6 Sol has the higher public score, 81.48 versus 57.92, and the 90% score intervals do not overlap.
- Workload cost
- A complete comparable API-rate estimate is not available for both models.
- Context tradeoff
- GPT-5.6 Sol has the larger documented window (1.05M).
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 evidence30 rows
Agentic
Terminal-Bench 2.0
GPT-5.6 Sol91.9%SourceMiMo-V2.565.8%SourceGPT-5.6 Sol leads this result
BrowseComp
GPT-5.6 Sol92.2%SourceMiMo-V2.5—Not directly comparable
OSWorld 2.0
GPT-5.6 Sol62.6%SourceMiMo-V2.5—Not directly comparable
CyberGym
GPT-5.6 Sol84.5%SourceMiMo-V2.5—Not directly comparable
ExploitGym
GPT-5.6 Sol33.7%SourceMiMo-V2.5—Not directly comparable
Toolathlon
GPT-5.6 Sol58%SourceMiMo-V2.5—Not directly comparable
Claw-Eval
GPT-5.6 Sol—MiMo-V2.562.3%SourceNot directly comparable
MM-ClawBench
GPT-5.6 Sol—MiMo-V2.523.8%SourceNot directly comparable
Gert Labs
GPT-5.6 Sol—MiMo-V2.546.89%SourceNot directly comparable
ResearchClawBench
GPT-5.6 Sol—MiMo-V2.516.9%SourceNot directly comparable
Coding
SWE-bench Pro
GPT-5.6 Sol64.6%SourceMiMo-V2.556.1%SourceGPT-5.6 Sol leads this result
Terminal-Bench 2.0
GPT-5.6 Sol91.9%SourceMiMo-V2.565.8%SourceGPT-5.6 Sol leads this result
deepSwe
GPT-5.6 Sol72.7%SourceMiMo-V2.5—Not directly comparable
FrontierCode 1.1 Extended
GPT-5.6 Sol60.6%SourceMiMo-V2.5—Not directly comparable
cursorBench32
GPT-5.6 Sol67.2%SourceMiMo-V2.5—Not directly comparable
VulcanBench v3
GPT-5.6 Sol87.0%SourceMiMo-V2.5—Not directly comparable
Reasoning
Knowledge
Math
Multimodal
Frequently asked questions
Which is better, GPT-5.6 Sol or MiMo-V2.5?
GPT-5.6 Sol has the higher public score, 81.48 versus 57.92, and the 90% score intervals do not overlap. That is the clearest overall quality signal in the current public data.
Which is better for coding, GPT-5.6 Sol or MiMo-V2.5?
GPT-5.6 Sol leads the like-for-like coding comparison across 1 shared weighted benchmark row.
Which is better for agentic tasks, GPT-5.6 Sol or MiMo-V2.5?
The current agentic tasks 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 costs less, GPT-5.6 Sol or MiMo-V2.5?
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, GPT-5.6 Sol or MiMo-V2.5?
GPT-5.6 Sol has the larger documented context window: 1.05M, compared with 1M.
Related comparisons
Last updated August 10, 2026
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