Skip to content

gpt-oss-120b vs Qwen3.7 Flash

gpt-oss-120b

OpenAI

40#207
vs
Qwen3.7 Flash

Alibaba

40#208
Signal-by-Signal Comparison
Signalgpt-oss-120bDeltaQwen3.7 Flash
Capabilities
67
-17
83
Benchmarks
46
+46
0
Pricing
100
0
100
Context window size
81
-14
95
Recency
68
-32
100
Output Capacity
85
+5
80
Overall Result
2 wins
of 6
4 wins
Qwen3.7 Flash wins 4 of 6 signals

Score History

Score History (24 data points)
gpt-oss-120bQwen3.7 Flash
gpt-oss-120b

40.4

current score

Leader

gpt-oss-120b

right now

Qwen3.7 Flash

40

current score

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

gpt-oss-120b

OpenAI

Per request$0.000122
Daily$0.41
Monthly$12.20
Annual$146.40

Qwen3.7 Flash

Alibaba

Best Value
Per request$0.000095
Daily$0.32
Monthly$9.50
Annual$114.00

Qwen3.7 Flash saves you $2.70/month

That's $32.40/year compared to gpt-oss-120b at your current usage level of 100K calls/month.

22% cheaper
Choose Qwen3.7 Flash for cost optimization

gpt-oss-120b pricing:
Input:$0.04/M tokens
Output:$0.17/M tokens
Qwen3.7 Flash pricing:
Input:$0.03/M tokens
Output:$0.13/M tokens
Winner
gpt-oss-120b

OpenAI

40

Composite Score

Qwen3.7 Flash

Alibaba

40

Composite Score

Signal-by-Signal Comparison
Metricgpt-oss-120bQwen3.7 FlashWinner
Overall Score
40
40
gpt-oss-120b
Rank#207#208
gpt-oss-120b
Quality Rank#207#208
gpt-oss-120b
Adoption Rank#207#208
gpt-oss-120b
Parameters120B----
Context Window131K1000K
Qwen3.7 Flash
Pricing$0.04/$0.17/M$0.03/$0.13/M--
Signal Scores
Capabilities
67
83
Qwen3.7 Flash
Benchmarks
46
--
gpt-oss-120b
Pricing
100
100
Qwen3.7 Flash
Context window size
81
95
Qwen3.7 Flash
Recency
68
100
Qwen3.7 Flash
Output Capacity
85
80
gpt-oss-120b
Benchmark Head-to-Head(2 benchmarks)
gpt-oss-120b: 0Qwen3.7 Flash: 0
gpt-oss-120b
Qwen3.7 Flash
Normalized 0-100%
SWE-bench Verified
26%-
Arena Elo
1352-
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-oss-120bEntry Level

Scores 40/100 (rank #207), placing it in the top 29% of all 290 models tracked.

Raw Quality0/100
Cost Efficiency0/100
Speed0/100
Qwen3.7 FlashEntry Level

Scores 40/100 (rank #208), placing it in the top 29% 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-oss-120b when you need:

  • Step-by-step reasoning and chain-of-thought problem solving
  • Self-hosted deployments where you need full control over the model

Choose Qwen3.7 Flash when you need:

  • Processing long documents or large codebases (1000K token context)
  • Multimodal workflows that require image understanding
  • Step-by-step reasoning and chain-of-thought problem solving
Cost-Performance Analysis
gpt-oss-120b
Input cost$0.04/M tokens
Output cost$0.17/M tokens
Cost per quality point$0.005
Est. monthly (1M tokens/day)$3.10
Qwen3.7 FlashBest Value
Input cost$0.03/M tokens
Output cost$0.13/M tokens
Cost per quality point$0.004
Est. monthly (1M tokens/day)$2.40

Qwen3.7 Flash offers 23% better value per quality point. At 1M tokens/day, you'd spend $2.40/month with Qwen3.7 Flash vs $3.10/month with gpt-oss-120b - a $0.70 monthly difference.

Latency & Speed
gpt-oss-120bFaster
Speed score0/100
Qwen3.7 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-oss-120b

Customer support chatbot

Suitable for user-facing chat with competitive response times. Qwen3.7 Flash also offers lower per-token costs for high-volume support

gpt-oss-120b

Long document analysis

Larger context window (1000K tokens) can process longer documents, contracts, and research papers in a single pass

Qwen3.7 Flash

Batch data extraction

Lower output pricing ($0.13/M) reduces costs when processing thousands of records daily

Qwen3.7 Flash

Creative writing & content

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

gpt-oss-120b

Image understanding & OCR

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

Qwen3.7 Flash
Which Should You Choose?
Our recommendation:
gpt-oss-120b

gpt-oss-120b and Qwen3.7 Flash are extremely close in overall performance (only 0.3999999999999986 points apart). Your best choice depends entirely on which specific strengths matter most for your use case.

gpt-oss-120b
Recommended

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 - 23% lower pricing; better value at scale
Capability Comparison
Capabilitygpt-oss-120bQwen3.7 Flash
Vision (Image Input)differs
Function Calling
Streaming
JSON Mode
Reasoning
Web Search
Image Output
Monthly Cost Calculator
1,000tokens (600 in / 400 out)
100requests/day (3,000/month)

gpt-oss-120b

OpenAI

$0.2706
estimated monthly cost

Qwen3.7 Flash

Alibaba

Best Value
$0.2100
estimated monthly cost

Qwen3.7 Flash saves you $0.0606/month

That's 22% cheaper than gpt-oss-120b 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-oss-120bQwen3.7 Flash
Context Window131K1M
Max Output Tokens131,07265,536
Open SourceYesNo
CreatedAug 5, 2025Jul 27, 2026
Last updated: 14m ago

Related comparisons

gpt-oss-120b vs Qwen3.7 Flash (2026) | LM Market Cap