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GPT-6 Sol (batch) vs Qwen3.8 Omni Flash

GPT-6 Sol (batch)

OpenAI

40#252
vs
Qwen3.8 Omni Flash

Alibaba

40#254
Signal-by-Signal Comparison
SignalGPT-6 Sol (batch)DeltaQwen3.8 Omni Flash
Capabilities
100
+17
83
Pricing
95
-4
100
Context window size
96
+0
95
Recency
100
--
100
Output Capacity
82
0
82
Overall Result
2 wins
of 5
2 wins
It's a tie - both models win 2 signals each

Score History

Score History (2 data points)
GPT-6 Sol (batch)Qwen3.8 Omni Flash
GPT-6 Sol (batch)

40

current score

Leader

Tied

right now

Qwen3.8 Omni Flash

40

current score

LMMarketCap.com
Interactive Price Comparison
100Kcalls/month
1,000tokens (~1,333 chars)
500tokens (~667 chars)

GPT-6 Sol (batch)

OpenAI

Per request$0.003500
Daily$11.67
Monthly$350.00
Annual$4200.00

Qwen3.8 Omni Flash

Alibaba

Best Value
Per request$0.000385
Daily$1.28
Monthly$38.50
Annual$462.00

Qwen3.8 Omni Flash saves you $311.50/month

That's $3738.00/year compared to GPT-6 Sol (batch) at your current usage level of 100K calls/month.

89% cheaper
Choose Qwen3.8 Omni Flash for cost optimization

GPT-6 Sol (batch) pricing:
Input:$1.00/M tokens
Output:$5.00/M tokens
Qwen3.8 Omni Flash pricing:
Input:$0.15/M tokens
Output:$0.47/M tokens
Tie
GPT-6 Sol (batch)

OpenAI

40

Composite Score

Tie
Qwen3.8 Omni Flash

Alibaba

40

Composite Score

Signal-by-Signal Comparison
MetricGPT-6 Sol (batch)Qwen3.8 Omni FlashWinner
Overall Score
40
40
--
Rank#252#254
GPT-6 Sol (batch)
Quality Rank#252#254
GPT-6 Sol (batch)
Adoption Rank#252#254
GPT-6 Sol (batch)
Parameters------
Context Window1050K1000K
GPT-6 Sol (batch)
Pricing$1.00/$5.00/M$0.15/$0.47/M--
Signal Scores
Capabilities
100
83
GPT-6 Sol (batch)
Pricing
95
100
Qwen3.8 Omni Flash
Context window size
96
95
GPT-6 Sol (batch)
Recency
100
100
GPT-6 Sol (batch)
Output Capacity
82
82
Qwen3.8 Omni Flash
Benchmark Interpretation

Our score (0-100) is driven by benchmark performance (90%) from Arena Elo ratings, MMLU, GPQA, HumanEval, SWE-bench, and 15+ standardized evaluations. Capabilities and context window serve as tiebreakers (10%). Learn more about our methodology.

GPT-6 Sol (batch)Entry Level

Scores 40/100 (rank #252), placing it in the top 13% of all 290 models tracked.

Raw Quality0/100
Cost Efficiency0/100
Speed0/100
Qwen3.8 Omni FlashEntry Level

Scores 40/100 (rank #254), placing it in the top 13% of all 290 models tracked.

Raw Quality0/100
Cost Efficiency0/100
Speed0/100

With only a 0-point gap, these models are in the same performance tier. The practical difference in output quality is minimal - your choice should depend on pricing, latency requirements, and specific feature needs.

When to Use Each Model

Choose GPT-6 Sol (batch) when you need:

  • Step-by-step reasoning and chain-of-thought problem solving

Choose Qwen3.8 Omni Flash when you need:

  • High-volume production workloads where API costs must be minimized
  • Step-by-step reasoning and chain-of-thought problem solving
Cost-Performance Analysis
GPT-6 Sol (batch)
Input cost$1.00/M tokens
Output cost$5.00/M tokens
Cost per quality point$0.150
Est. monthly (1M tokens/day)$90.00
Qwen3.8 Omni FlashBest Value
Input cost$0.15/M tokens
Output cost$0.47/M tokens
Cost per quality point$0.015
Est. monthly (1M tokens/day)$9.30

Qwen3.8 Omni Flash offers 90% better value per quality point. At 1M tokens/day, you'd spend $9.30/month with Qwen3.8 Omni Flash vs $90.00/month with GPT-6 Sol (batch) - a $80.70 monthly difference.

Latency & Speed
GPT-6 Sol (batch)Faster
Speed score0/100
Qwen3.8 Omni Flash
Speed score0/100

Both models have comparable response speeds. For most applications, the latency difference is negligible.

When latency matters most: Interactive chatbots, IDE code completion, real-time translation, and user-facing applications where response time directly impacts experience. For batch processing, background summarization, or offline analysis, latency is less critical.

Example Use Cases

Code generation & review

Based on overall model capabilities and architecture for coding tasks like generating functions, debugging, and refactoring

GPT-6 Sol (batch)

Customer support chatbot

Suitable for user-facing chat with competitive response times. Qwen3.8 Omni Flash also offers lower per-token costs for high-volume support

GPT-6 Sol (batch)

Long document analysis

Larger context window (1050K tokens) can process longer documents, contracts, and research papers in a single pass

GPT-6 Sol (batch)

Batch data extraction

Lower output pricing ($0.47/M) reduces costs when processing thousands of records daily

Qwen3.8 Omni Flash

Creative writing & content

Higher overall composite score (40/100) correlates with better nuance, coherence, and style in long-form content

GPT-6 Sol (batch)

Image understanding & OCR

Supports vision input - can analyze screenshots, diagrams, photos, and scanned documents directly

GPT-6 Sol (batch)
Which Should You Choose?
Our recommendation:
GPT-6 Sol (batch)

GPT-6 Sol (batch) and Qwen3.8 Omni Flash are extremely close in overall performance (only 0 points apart). Your best choice depends entirely on which specific strengths matter most for your use case.

by OpenAI

  • Choose for Quality - Marginally better benchmark scores; both are excellent
  • Choose for Reliability - Higher uptime and faster response speeds
  • Choose for Prototyping - Stronger community support and better developer experience
  • Choose for Production - Wider enterprise adoption and proven at scale

by Alibaba

  • Choose for Cost - 90% lower pricing; better value at scale
Capability Comparison
CapabilityGPT-6 Sol (batch)Qwen3.8 Omni Flash
Vision (Image Input)
Function Calling
Streaming
JSON Mode
Reasoning
Web Searchdiffers
Image Output
Monthly Cost Calculator
1,000tokens (600 in / 400 out)
100requests/day (3,000/month)

GPT-6 Sol (batch)

OpenAI

$7.80
estimated monthly cost

Qwen3.8 Omni Flash

Alibaba

Best Value
$0.8340
estimated monthly cost

Qwen3.8 Omni Flash saves you $6.97/month

That's 89% cheaper than GPT-6 Sol (batch) at 1,000 tokens/request and 100 requests/day.

Assumes 60% input / 40% output token ratio per request. Actual costs may vary based on your usage pattern.

Parameters & Context
ParameterGPT-6 Sol (batch)Qwen3.8 Omni Flash
Context Window1.1M1M
Max Output Tokens128,000131,072
Open SourceNoNo
CreatedSep 22, 2026Sep 21, 2026
Last updated: 12m ago

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GPT-6 Sol (batch) vs Qwen3.8 Omni Flash (2026) | LM Market Cap