Model comparison
GPT-5.2-Codex vs Mistral 8x7B
Head-to-head evidence from 0 shared benchmark results across 0 categories. Overall scores shown here use the public BenchAlign v5 ranking lane.
Public leaderboard positions: GPT-5.2-Codex #58 (Supported); Mistral 8x7B #146 (Estimated). Intervals and evidence labels describe ranking uncertainty, not a guarantee for a specific workload.
Evidence parity. GPT-5.2-Codex and Mistral 8x7B share 0 comparable benchmark results. 0 of 8 categories are comparable. 15 results are unique to GPT-5.2-Codex; 0 to Mistral 8x7B.
Updated July 21, 2026- Shared results
- 0
- GPT-5.2-Codex only
- 15
- Mistral 8x7B only
- 0
- Comparable categories
- 0 / 8
Benchmark data for GPT-5.2-Codex and Mistral 8x7B is coming soon on BenchLM.
Confidence note. This is a partial-evidence comparison with 0 shared benchmark results across 0 evidence categories; 0 of 8 categories currently have scoreable aggregates for both models. Treat the verdict as directional until coverage is more balanced.
Why this result
BenchLM does not have sourced benchmark coverage for Mistral 8x7B yet. This comparison is currently limited to metadata such as context window, reasoning mode, and pricing where available.
GPT-5.2-Codex is priced at $1.75 input / $14.00 output per 1M tokens, versus $0.00 input / $0.00 output per 1M tokens for Mistral 8x7B. GPT-5.2-Codex has the larger context window at 400K, compared with 32K for Mistral 8x7B.
Operational comparison
Runtime and commercial metrics are compared only when both models have a complete sourced value.
| Metric | GPT-5.2-Codex | Mistral 8x7B | Comparison |
|---|---|---|---|
| Input / output priceUSD per 1M tokens | GPT-5.2-Codex$1.75 input / $14 output | Mistral 8x7B$0 input / $0 output | Mistral 8x7B has the lower combined listed price. |
| Generation speedtokens per second | GPT-5.2-Codex123 tok/s | Mistral 8x7BNot available | A complete speed comparison is not available. |
| First-answer latencyseconds to first token | GPT-5.2-Codex87.34 s | Mistral 8x7BNot available | A complete latency comparison is not available. |
| Context windowmaximum listed tokens | GPT-5.2-Codex400K | Mistral 8x7B32K | GPT-5.2-Codex lists the larger context window. |
Benchmark Deep Dive
Agentic3 benchmarks
Coding2 benchmarks
Reasoning2 benchmarks
Knowledge6 benchmarks
| Benchmark | GPT-5.2-Codex | Mistral 8x7B | Result |
|---|---|---|---|
| Artificial Analysis Intelligence IndexSource | 40.1% | — | Not comparable |
| AA-GPQA DiamondSource | 89.9% | — | Not comparable |
| AA-HLESource | 33.5% | — | Not comparable |
| AA-Omniscience IndexSource | -2.5% | — | Not comparable |
| AA-Omniscience AccuracySource | 40.7% | — | Not comparable |
| AA-Omniscience Hallucination RateSource | 72.8% | — | Not comparable |
Multimodal1 benchmarks
| Benchmark | GPT-5.2-Codex | Mistral 8x7B | Result |
|---|---|---|---|
| AA-MMMU-ProSource | 76.3% | — | Not comparable |
Inst. Following1 benchmarks
| Benchmark | GPT-5.2-Codex | Mistral 8x7B | Result |
|---|---|---|---|
| AA-IFBenchSource | 77.6% | — | Not comparable |
Frequently Asked Questions (3)
Can I compare GPT-5.2-Codex and Mistral 8x7B on BenchLM yet?
Not fully yet. BenchLM is tracking both models, but the sourced benchmark breakdown for this comparison is still coming soon.
Why does this comparison show “coming soon”?
BenchLM only shows category winners and benchmark-level calls when we have sourced results that can be compared fairly. For these models, the public benchmark coverage is not complete enough yet.
What data is available for GPT-5.2-Codex and Mistral 8x7B today?
GPT-5.2-Codex: $1.75 input / $14.00 output per 1M tokens Mistral 8x7B: $0.00 input / $0.00 output per 1M tokens Both model pages still include creator, context window, reasoning mode, and other metadata while benchmark coverage fills in.
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