Model comparison
GPT-5.3 Codex vs MiMo-V2-Flash
Head-to-head evidence from 12 shared benchmark results across 5 categories. Overall scores shown here use the public BenchAlign v5 ranking lane.
Public leaderboard positions: GPT-5.3 Codex #26 (Supported); MiMo-V2-Flash #91 (Supported). Intervals and evidence labels describe ranking uncertainty, not a guarantee for a specific workload.
Evidence parity. GPT-5.3 Codex and MiMo-V2-Flash share 12 comparable benchmark results. 1 of 8 categories are comparable. 9 results are unique to GPT-5.3 Codex; 7 to MiMo-V2-Flash.
Updated July 20, 2026- Shared results
- 12
- GPT-5.3 Codex only
- 9
- MiMo-V2-Flash only
- 7
- Comparable categories
- 1 / 8
Pick GPT-5.3 Codex if you want the stronger benchmark profile. MiMo-V2-Flash only becomes the better choice if coding is the priority or you want the cheaper token bill.
Confidence note. This is a partial-evidence comparison with 12 shared benchmark results across 5 evidence categories; 1 of 8 categories currently have scoreable aggregates for both models. Treat the verdict as directional until coverage is more balanced.
Why this result
GPT-5.3 Codex is clearly ahead on the BenchAlign aggregate, 66.69 to 54.06. The gap is large enough that you do not need to squint at the spreadsheet to see the difference.
GPT-5.3 Codex is also the more expensive model on tokens at $1.75 input / $14.00 output per 1M tokens, versus $0.00 input / $0.00 output per 1M tokens for MiMo-V2-Flash. That is roughly Infinityx on output cost alone. GPT-5.3 Codex gives you the larger context window at 400K, compared with 256K for MiMo-V2-Flash.
Category breakdown
Exact category averages are shown below. Not measured means BenchLM does not have enough sourced public coverage for that model and category.
| Category | GPT-5.3 Codex | Δ | MiMo-V2-Flash |
|---|---|---|---|
| Coding | GPT-5.3 Codex67.2 | Margin→ 6.2 | MiMo-V2-Flash73.4 |
| Agentic | GPT-5.3 Codex71.4 | MarginNo overlap | MiMo-V2-FlashNot measured |
| Knowledge | GPT-5.3 CodexNot measured | MarginNo overlap | MiMo-V2-Flash84.7 |
Decisive benchmark drivers
The largest measured benchmark gaps in this matchup, with exact reported values.
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- Source ↗
SWE-bench Verified
CodingA 85%B 73.4%Winner: GPT-5.3 CodexΔ 11.6SWE-bench Verified: GPT-5.3 Codex scored 85%; MiMo-V2-Flash scored 73.4%. GPT-5.3 Codex wins this benchmark.
Operational comparison
Runtime and commercial metrics are compared only when both models have a complete sourced value.
| Metric | GPT-5.3 Codex | MiMo-V2-Flash | Comparison |
|---|---|---|---|
| Input / output priceUSD per 1M tokens | GPT-5.3 Codex$1.75 input / $14 output | MiMo-V2-Flash$0 input / $0 output | MiMo-V2-Flash has the lower combined listed price. |
| Generation speedtokens per second | GPT-5.3 Codex79 tok/s | MiMo-V2-Flash129 tok/s | MiMo-V2-Flash has the higher measured throughput. |
| First-answer latencyseconds to first token | GPT-5.3 Codex88.26 s | MiMo-V2-Flash2.14 s | MiMo-V2-Flash reaches the first token sooner. |
| Context windowmaximum listed tokens | GPT-5.3 Codex400K | MiMo-V2-Flash256K | GPT-5.3 Codex lists the larger context window. |
Benchmark Deep Dive
Agentic8 benchmarks
| Benchmark | GPT-5.3 Codex | MiMo-V2-Flash | Result |
|---|---|---|---|
| Terminal-Bench 2.0Source | 77.3% | — | Not comparable |
| OSWorld-VerifiedSource | 64.7% | — | Not comparable |
| τ²-bench resultsSource | 86% | 83.9% | GPT-5.3 Codex leads |
| Gert LabsSource | 57.47% | — | Not comparable |
| JobBenchSource | 33.7% | — | Not comparable |
| AA Agentic IndexSource | — | 12.0% | Not comparable |
| GDPval-AASource | — | 16.7% | Not comparable |
| GDPval-AASource | — | 833 | Not comparable |
CodingMiMo-V2-Flash wins6 benchmarks
| Benchmark | GPT-5.3 Codex | MiMo-V2-Flash | Result |
|---|---|---|---|
| SWE-bench VerifiedSource | 85% | 73.4% | GPT-5.3 Codex leads |
| SWE-bench ProSource | 56.8% | — | Not comparable |
| SWE-RebenchSource | 58.2% | — | Not comparable |
| Vibe Code BenchSource | 61.77% | — | Not comparable |
| AA-SciCodeSource | 53.2% | 25.9% | GPT-5.3 Codex leads |
| AA Coding IndexSource | — | 49.8% | Not comparable |
Reasoning2 benchmarks
Knowledge8 benchmarks
| Benchmark | GPT-5.3 Codex | MiMo-V2-Flash | Result |
|---|---|---|---|
| Artificial Analysis Intelligence IndexSource | 44.3% | 24.7% | GPT-5.3 Codex leads |
| AA-GPQA DiamondSource | 91.5% | 65.6% | GPT-5.3 Codex leads |
| AA-HLESource | 39.9% | 8.0% | GPT-5.3 Codex leads |
| AA-Omniscience IndexSource | 9.9% | -48.5% | GPT-5.3 Codex leads |
| AA-Omniscience AccuracySource | 51.8% | 15.2% | GPT-5.3 Codex leads |
| AA-Omniscience Hallucination RateSource | 86.9% | 75.1% | MiMo-V2-Flash leads |
| GPQASource | — | 83.7% | Not comparable |
| MMLU-ProSource | — | 84.9% | Not comparable |
Math1 benchmarks
| Benchmark | GPT-5.3 Codex | MiMo-V2-Flash | Result |
|---|---|---|---|
| AIME 2025Source | — | 94.1% | Not comparable |
Multimodal2 benchmarks
Inst. Following1 benchmarks
| Benchmark | GPT-5.3 Codex | MiMo-V2-Flash | Result |
|---|---|---|---|
| AA-IFBenchSource | 75.4% | 39.9% | GPT-5.3 Codex leads |
Frequently Asked Questions (2)
Which is better, GPT-5.3 Codex or MiMo-V2-Flash?
GPT-5.3 Codex is ahead on BenchLM's BenchAlign leaderboard, 66.69 to 54.06. The biggest single separator in this matchup is SWE-bench Verified, where the scores are 85% and 73.4%.
Which is better for coding, GPT-5.3 Codex or MiMo-V2-Flash?
MiMo-V2-Flash has the edge for coding in this comparison, averaging 73.4 versus 67.2. Inside this category, AA-SciCode is the benchmark that creates the most daylight between them.
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